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  • Proliant server will not accept new hard disks in RAID 1+0?

    - by Leigh
    I have a HP ProLiant DL380 G5, I have two logical drives configured with RAID. I have one logical drive RAID 1+0 with two 72 gb 10k sas 1 port spare no 376597-001. I had one hard disk fail and ordered a replacement. The configuration utility showed error and would not rebuild the RAID. I presumed a hard disk fault and ordered a replacement again. In the mean time I put the original failed disk back in the server and this started rebuilding. Currently shows ok status however in the log I can see hardware errors. The new disk has come and I again have the same problem of not accepting the hard disk. I have updated the P400 controller with the latest firmware 7.24 , but still no luck. The only difference I can see is the original drive has firmware 0103 (same as the RAID drive) and the new one has HPD2. Any advice would be appreciated. Thanks in advance Logs from server ctrl all show config Smart Array P400 in Slot 1 (sn: PAFGK0P9VWO0UQ) array A (SAS, Unused Space: 0 MB) logicaldrive 1 (68.5 GB, RAID 1, Interim Recovery Mode) physicaldrive 2I:1:1 (port 2I:box 1:bay 1, SAS, 73.5 GB, OK) physicaldrive 2I:1:2 (port 2I:box 1:bay 2, SAS, 72 GB, Failed array B (SAS, Unused Space: 0 MB) logicaldrive 2 (558.7 GB, RAID 5, OK) physicaldrive 1I:1:5 (port 1I:box 1:bay 5, SAS, 300 GB, OK) physicaldrive 2I:1:3 (port 2I:box 1:bay 3, SAS, 300 GB, OK) physicaldrive 2I:1:4 (port 2I:box 1:bay 4, SAS, 300 GB, OK) ctrl all show config detail Smart Array P400 in Slot 1 Bus Interface: PCI Slot: 1 Serial Number: PAFGK0P9VWO0UQ Cache Serial Number: PA82C0J9VWL8I7 RAID 6 (ADG) Status: Disabled Controller Status: OK Hardware Revision: E Firmware Version: 7.24 Rebuild Priority: Medium Expand Priority: Medium Surface Scan Delay: 15 secs Surface Scan Mode: Idle Wait for Cache Room: Disabled Surface Analysis Inconsistency Notification: Disabled Post Prompt Timeout: 0 secs Cache Board Present: True Cache Status: OK Cache Status Details: A cache error was detected. Run more information. Cache Ratio: 100% Read / 0% Write Drive Write Cache: Disabled Total Cache Size: 256 MB Total Cache Memory Available: 208 MB No-Battery Write Cache: Disabled Battery/Capacitor Count: 0 SATA NCQ Supported: True Array: A Interface Type: SAS Unused Space: 0 MB Status: Failed Physical Drive Array Type: Data One of the drives on this array have failed or has Logical Drive: 1 Size: 68.5 GB Fault Tolerance: RAID 1 Heads: 255 Sectors Per Track: 32 Cylinders: 17594 Strip Size: 128 KB Full Stripe Size: 128 KB Status: Interim Recovery Mode Caching: Enabled Unique Identifier: 600508B10010503956574F305551 Disk Name: \\.\PhysicalDrive0 Mount Points: C:\ 68.5 GB Logical Drive Label: A0100539PAFGK0P9VWO0UQ0E93 Mirror Group 0: physicaldrive 2I:1:2 (port 2I:box 1:bay 2, S Mirror Group 1: physicaldrive 2I:1:1 (port 2I:box 1:bay 1, S Drive Type: Data physicaldrive 2I:1:1 Port: 2I Box: 1 Bay: 1 Status: OK Drive Type: Data Drive Interface Type: SAS Size: 73.5 GB Rotational Speed: 10000 Firmware Revision: 0103 Serial Number: B379P8C006RK Model: HP DG072A9B7 PHY Count: 2 PHY Transfer Rate: Unknown, Unknown physicaldrive 2I:1:2 Port: 2I Box: 1 Bay: 2 Status: Failed Drive Type: Data Drive Interface Type: SAS Size: 72 GB Rotational Speed: 15000 Firmware Revision: HPD9 Serial Number: D5A1PCA04SL01244 Model: HP EH0072FARUA PHY Count: 2 PHY Transfer Rate: Unknown, Unknown Array: B Interface Type: SAS Unused Space: 0 MB Status: OK Array Type: Data Logical Drive: 2 Size: 558.7 GB Fault Tolerance: RAID 5 Heads: 255 Sectors Per Track: 32 Cylinders: 65535 Strip Size: 64 KB Full Stripe Size: 128 KB Status: OK Caching: Enabled Parity Initialization Status: Initialization Co Unique Identifier: 600508B10010503956574F305551 Disk Name: \\.\PhysicalDrive1 Mount Points: E:\ 558.7 GB Logical Drive Label: AF14FD12PAFGK0P9VWO0UQD007 Drive Type: Data physicaldrive 1I:1:5 Port: 1I Box: 1 Bay: 5 Status: OK Drive Type: Data Drive Interface Type: SAS Size: 300 GB Rotational Speed: 10000 Firmware Revision: HPD4 Serial Number: 3SE07QH300009923X1X3 Model: HP DG0300BALVP Current Temperature (C): 32 Maximum Temperature (C): 45 PHY Count: 2 PHY Transfer Rate: Unknown, Unknown physicaldrive 2I:1:3 Port: 2I Box: 1 Bay: 3 Status: OK Drive Type: Data Drive Interface Type: SAS Size: 300 GB Rotational Speed: 10000 Firmware Revision: HPD4 Serial Number: 3SE0AHVH00009924P8F3 Model: HP DG0300BALVP Current Temperature (C): 34 Maximum Temperature (C): 47 PHY Count: 2 PHY Transfer Rate: Unknown, Unknown physicaldrive 2I:1:4 Port: 2I Box: 1 Bay: 4 Status: OK Drive Type: Data Drive Interface Type: SAS Size: 300 GB Rotational Speed: 10000 Firmware Revision: HPD4 Serial Number: 3SE08NAK00009924KWD6 Model: HP DG0300BALVP Current Temperature (C): 35 Maximum Temperature (C): 47 PHY Count: 2 PHY Transfer Rate: Unknown, Unknown

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  • How do I allow mysqld to use more than 24.9% of my cpu?

    - by Joseph Yancey
    I have a Web server running on RHEL that is running Apache and MySQL. It has a Quad core 3.2Ghz Xeon CPU and 8 Gigs of RAM Most of the time, we don't have any issues at all. Our web application is very database intensive. When our usage gets pretty heavy MySQL will peg out at using 24.9% of the cpu. Most of the time, it hangs around below 5%. I have speculated that it is only using one core of the CPU and it is pegging out that core but TOP shows me in the cpu column that mysqld changes cores even while the usage stays at 24.9%. When it does this MySQL gets painfully slow as it is queuing up queries Is there some magic configuration that will tell mysql to use more cpu when it needs to? Also, any other advice on my configuration would be helpful. We run two applications on this server. One that runs Innodb but doesn't get much usage (it has been replaced by the other app), and one that runs MyIsam and gets lots of use. Overall, our whole mysql data directory is something like 13Gigs if that matters at all. Here is my config: [root@ProductionLinux root]# cat /etc/my.cnf [mysqld] server-id = 71 log-bin = /var/log/mysql/mysql-bin.log binlog-do-db = oldapplication binlog-do-db = newapplication binlog-do-db = support thread_cache_size = 30 key_buffer_size = 256M table_cache = 256 sort_buffer_size = 4M read_buffer_size = 1M skip-name-resolve innodb_data_home_dir = /usr/local/mysql/data/ innodb_data_file_path = InnoDB:100M:autoextend set-variable = innodb_buffer_pool_size=70M set-variable = innodb_additional_mem_pool_size=10M set-variable = max_connections=500 innodb_log_group_home_dir = /usr/local/mysql/data innodb_log_arch_dir = /usr/local/mysql/data set-variable = innodb_log_file_size=20M set-variable = innodb_log_buffer_size=8M innodb_flush_log_at_trx_commit = 1 log-queries-not-using-indexes log-error = /var/log/mysql/mysql-error.log mysql show variables; +---------------------------------+-----------------------------------------------------------------------------+ | Variable_name | Value | +---------------------------------+-----------------------------------------------------------------------------+ | auto_increment_increment | 1 | | auto_increment_offset | 1 | | automatic_sp_privileges | ON | | back_log | 50 | | basedir | /usr/local/mysql-standard-5.0.18-linux-x86_64-glibc23/ | | binlog_cache_size | 32768 | | bulk_insert_buffer_size | 8388608 | | character_set_client | latin1 | | character_set_connection | latin1 | | character_set_database | latin1 | | character_set_results | latin1 | | character_set_server | latin1 | | character_set_system | utf8 | | character_sets_dir | /usr/local/mysql-standard-5.0.18-linux-x86_64-glibc23/share/mysql/charsets/ | | collation_connection | latin1_swedish_ci | | collation_database | latin1_swedish_ci | | collation_server | latin1_swedish_ci | | completion_type | 0 | | concurrent_insert | 1 | | connect_timeout | 5 | | datadir | /usr/local/mysql/data/ | | date_format | %Y-%m-%d | | datetime_format | %Y-%m-%d %H:%i:%s | | default_week_format | 0 | | delay_key_write | ON | | delayed_insert_limit | 100 | | delayed_insert_timeout | 300 | | delayed_queue_size | 1000 | | div_precision_increment | 4 | | engine_condition_pushdown | OFF | | expire_logs_days | 0 | | flush | OFF | | flush_time | 0 | | | ft_max_word_len | 84 | | ft_min_word_len | 4 | | ft_query_expansion_limit | 20 | | ft_stopword_file | (built-in) | | group_concat_max_len | 1024 | | have_archive | YES | | have_bdb | NO | | have_blackhole_engine | NO | | have_compress | YES | | have_crypt | YES | | have_csv | NO | | have_example_engine | NO | | have_federated_engine | NO | | have_geometry | YES | | have_innodb | YES | | have_isam | NO | | have_ndbcluster | NO | | have_openssl | NO | | have_query_cache | YES | | have_raid | NO | | have_rtree_keys | YES | | have_symlink | YES | | init_connect | | | init_file | | | init_slave | | | innodb_additional_mem_pool_size | 10485760 | | innodb_autoextend_increment | 8 | | innodb_buffer_pool_awe_mem_mb | 0 | | innodb_buffer_pool_size | 73400320 | | innodb_checksums | ON | | innodb_commit_concurrency | 0 | | innodb_concurrency_tickets | 500 | | innodb_data_file_path | InnoDB:100M:autoextend | | innodb_data_home_dir | /usr/local/mysql/data/ | | innodb_doublewrite | ON | | innodb_fast_shutdown | 1 | | innodb_file_io_threads | 4 | | innodb_file_per_table | OFF | | innodb_flush_log_at_trx_commit | 1 | | innodb_flush_method | | | innodb_force_recovery | 0 | | innodb_lock_wait_timeout | 50 | | innodb_locks_unsafe_for_binlog | OFF | | innodb_log_arch_dir | /usr/local/mysql/data | | innodb_log_archive | OFF | | innodb_log_buffer_size | 8388608 | | innodb_log_file_size | 20971520 | | innodb_log_files_in_group | 2 | | innodb_log_group_home_dir | /usr/local/mysql/data | | innodb_max_dirty_pages_pct | 90 | | innodb_max_purge_lag | 0 | | innodb_mirrored_log_groups | 1 | | innodb_open_files | 300 | | innodb_support_xa | ON | | innodb_sync_spin_loops | 20 | | innodb_table_locks | ON | | innodb_thread_concurrency | 20 | | innodb_thread_sleep_delay | 10000 | | interactive_timeout | 28800 | | join_buffer_size | 131072 | | key_buffer_size | 268435456 | | key_cache_age_threshold | 300 | | key_cache_block_size | 1024 | | key_cache_division_limit | 100 | | language | /usr/local/mysql-standard-5.0.18-linux-x86_64-glibc23/share/mysql/english/ | | large_files_support | ON | | large_page_size | 0 | | large_pages | OFF | | license | GPL | | local_infile | ON | | locked_in_memory | OFF | | log | OFF | | log_bin | ON | | log_bin_trust_function_creators | OFF | | log_error | /var/log/mysql/mysql-error.log | | log_slave_updates | OFF | | log_slow_queries | OFF | | log_warnings | 1 | | long_query_time | 10 | | low_priority_updates | OFF | | lower_case_file_system | OFF | | lower_case_table_names | 0 | | max_allowed_packet | 1048576 | | max_binlog_cache_size | 18446744073709551615 | | max_binlog_size | 1073741824 | | max_connect_errors | 10 | | max_connections | 500 | | max_delayed_threads | 20 | | max_error_count | 64 | | max_heap_table_size | 16777216 | | max_insert_delayed_threads | 20 | | max_join_size | 18446744073709551615 | | max_length_for_sort_data | 1024 | | max_relay_log_size | 0 | | max_seeks_for_key | 18446744073709551615 | | max_sort_length | 1024 | | max_sp_recursion_depth | 0 | | max_tmp_tables | 32 | | max_user_connections | 0 | | max_write_lock_count | 18446744073709551615 | | multi_range_count | 256 | | myisam_data_pointer_size | 6 | | myisam_max_sort_file_size | 9223372036854775807 | | myisam_recover_options | OFF | | myisam_repair_threads | 1 | | myisam_sort_buffer_size | 8388608 | | myisam_stats_method | nulls_unequal | | net_buffer_length | 16384 | | net_read_timeout | 30 | | net_retry_count | 10 | | net_write_timeout | 60 | | new | OFF | | old_passwords | OFF | | open_files_limit | 2510 | | optimizer_prune_level | 1 | | optimizer_search_depth | 62 | | pid_file | /usr/local/mysql/data/ProductionLinux.pid | | port | 3306 | | preload_buffer_size | 32768 | | protocol_version | 10 | | query_alloc_block_size | 8192 | | query_cache_limit | 1048576 | | query_cache_min_res_unit | 4096 | | query_cache_size | 0 | | query_cache_type | ON | | query_cache_wlock_invalidate | OFF | | query_prealloc_size | 8192 | | range_alloc_block_size | 2048 | | read_buffer_size | 1044480 | | read_only | OFF | | read_rnd_buffer_size | 262144 | | relay_log_purge | ON | | relay_log_space_limit | 0 | | rpl_recovery_rank | 0 | | secure_auth | OFF | | server_id | 71 | | skip_external_locking | ON | | skip_networking | OFF | | skip_show_database | OFF | | slave_compressed_protocol | OFF | | slave_load_tmpdir | /tmp/ | | slave_net_timeout | 3600 | | slave_skip_errors | OFF | | slave_transaction_retries | 10 | | slow_launch_time | 2 | | socket | /tmp/mysql.sock | | sort_buffer_size | 4194296 | | sql_mode | | | sql_notes | ON | | sql_warnings | ON | | storage_engine | MyISAM | | sync_binlog | 0 | | sync_frm | ON | | sync_replication | 0 | | sync_replication_slave_id | 0 | | sync_replication_timeout | 10 | | system_time_zone | CST | | table_cache | 256 | | table_lock_wait_timeout | 50 | | table_type | MyISAM | | thread_cache_size | 30 | | thread_stack | 262144 | | time_format | %H:%i:%s | | time_zone | SYSTEM | | timed_mutexes | OFF | | tmp_table_size | 33554432 | | tmpdir | | | transaction_alloc_block_size | 8192 | | transaction_prealloc_size | 4096 | | tx_isolation | REPEATABLE-READ | | updatable_views_with_limit | YES | | version | 5.0.18-standard-log | | version_comment | MySQL Community Edition - Standard (GPL) | | version_compile_machine | x86_64 | | version_compile_os | unknown-linux-gnu | | wait_timeout | 28800 | +---------------------------------+-----------------------------------------------------------------------------+ 210 rows in set (0.00 sec)

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  • Hard drive after PCB swap strange stuff

    - by ramyy
    I’ve done a PCB swap to my HDD. The HDD model is: WD6400AAKS-00A7B2. The original PCB PN matches the new one (first three letter groups), though the cache mismatches (16MB original, 8MB new). The Hardware store that made the swap told me it was hard to do the swap, they have done firmware adaptation. I can see that this firmware version does not match the original, (01.03B01 original, 05.04E05 new). Still I can see that the serial number and model of the drive is correct, the hard drive appeared normal in the BIOS, all the partitions show and everything appears normal. I have encountered three things though, I have left the drive non operated for 2-3 weeks after the swap to avoid corrupting the data or anything else the new PCB might cause, until I buy a new drive and backup the data. I got a drive, and when I powered the old drive manually (I have a laptop, I use a normal desktop power supply and a USB/SATA connector), I heard the motor start and I could hear ticking as if the motor’s somehow struggling to start, and then the motor sound starts again then the ticking, and so on.. I tried powering again it happened again. The third time it started normally and I could see everything normally. I took the chance and copied all the data over to the new drive. When I was done, I powered off the drive (after more than 25 hours of continuous operation), tried to power it up again and it did so normally, and so are the times I powered it up later; but I got very suspicious now. What could be the problem here? And what happened new, it used to power normally after the swap directly? The second thing that happened is that I found size differences with some files; some include movies, songs, (.iso) files for games, and programs. I could find the size is the same, but size on disk is a little more on the new drive for these files. . I’ve tried some of those files (with size differences) they worked fine. They are not too much but still make you suspicious of the integrity of the data copied; one cannot try if all files are working for about (580 GB) worth of data. I tried copying these files on the same partition they exist of the old drive; they are the same in size as when copied to the new drive (allocation unit size not the issue). I took an image of a partition (sector by sector including empty ones) and when I explore it, these file sizes are equal to the original (old drive); I copy them anywhere else their size on disk, increases, i.e becomes equal to the ones I copy from the old drive itself anywhere. Why the size difference and can one trust the integrity of the data?? The third thing is that when I connect my new external USB HDD, the partitions of the old HDD unmount and then mount again. Connected are: (USB mouse + Old HDD) then external HDD. Why that happens?? Considering the following: I compared the SMART reports from after the swap directly and after the copying, no error readings or reallocated sectors where reported. Here they are: http://www.image-share.com/ijpg-1939-219.html I later ran both WD data life guard tests and they came out passed. I’m worried for this drive since I must be sure the data is fine and safe on the new one, and I will consider it backup for the new one, since you can’t trust anything anymore. I hope you can forgive me for the length of the post, but couldn’t ignore any of the details, this hard drive contains very important data to me and I have to deal with the situation with great care.

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  • How to resolve: 'cmd' is not recognized as an internal or external command?

    - by qwer1234
    I have searched other forums to solve this error where it would either end with: 1.) re-install OS 2.) Setting path variable C:/Windows/System32 The latter did not work, and as you can probably imagine, I do not want to have to re-install my OS... I am running the command "mvn jetty:run" and the following is my stack trace, finishing with the message: "'cmd' is not recognized as an internal or external command, operable problem or batch file" as stated in the title of this question. [INFO] Scanning for projects... [INFO] ------------------------------------------------------------------------ [INFO] Building Test Tool [INFO] task-segment: [jetty:run] [INFO] ------------------------------------------------------------------------ [INFO] Preparing jetty:run [WARNING] Removing: run from forked lifecycle, to prevent recursive invocation. [INFO] [resources:resources] [WARNING] Using platform encoding (Cp1252 actually) to copy filtered resources, i.e. build is platform dependent! [INFO] Copying 32 resources [INFO] Copying 192 resources [INFO] [compiler:compile] [INFO] Compiling 1854 source files to C:\Development\global_stock_record\test\java\Turtle\target\classes [INFO] ------------------------------------------------------------------------ [ERROR] BUILD FAILURE [INFO] ------------------------------------------------------------------------ [INFO] Compilation failure C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\compilers\JavaScriptClassCompiler.java:[45,29] cannot find symbol symbol : class CompilerEnvirons location: package org.mozilla.javascript C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\compilers\JavaScriptClassCompiler.java:[47,29] cannot find symbol symbol : class ContextFactory location: package org.mozilla.javascript C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\compilers\JavaScriptClassCompiler.java:[49,39] cannot find symbol symbol : class ClassCompiler location: package org.mozilla.javascript.optimizer C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\compilers\JavaScriptClassCompiler.java:[181,55] cannot find symbol symbol : class CompilerEnvirons location: class net.sf.jasperreports.compilers.JavaScriptClassCompiler C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\export\JRXmlExporter.java:[99,26] package org.w3c.tools.codec does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\xml\JRBaseFactory.java:[26,34] package org.apache.commons.digester does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\xml\JRBaseFactory.java:[27,34] package org.apache.commons.digester does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\xml\JRBaseFactory.java:[34,47] cannot find symbol symbol: class ObjectCreationFactory public abstract class JRBaseFactory implements ObjectCreationFactory C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\xml\JRBaseFactory.java:[41,21] cannot find symbol symbol : class Digester location: class net.sf.jasperreports.engine.xml.JRBaseFactory C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\xml\JRBaseFactory.java:[47,8] cannot find symbol symbol : class Digester location: class net.sf.jasperreports.engine.xml.JRBaseFactory C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\xml\JRBaseFactory.java:[56,25] cannot find symbol symbol : class Digester location: class net.sf.jasperreports.engine.xml.JRBaseFactory C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\Code39Component.java:[28,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\BarcodeComponent.java:[41,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\Code39Component.java:[66,29] cannot find symbol symbol : class ChecksumMode location: class net.sf.jasperreports.components.barcode4j.Code39Component C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\BarcodeComponent.java:[179,29] cannot find symbol symbol : class HumanReadablePlacement location: class net.sf.jasperreports.components.barcode4j.BarcodeComponent C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\EAN128Component.java:[26,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\DataMatrixComponent.java:[26,45] package org.krysalis.barcode4j.impl.datamatrix does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\FourStateBarcodeComponent.java:[26,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\UPCAComponent.java:[28,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\UPCEComponent.java:[28,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\EAN13Component.java:[28,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\EAN8Component.java:[28,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\Interleaved2Of5Component.java:[28,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\EAN128Component.java:[57,29] cannot find symbol symbol : class ChecksumMode location: class net.sf.jasperreports.components.barcode4j.EAN128Component C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\DataMatrixComponent.java:[62,22] cannot find symbol symbol : class SymbolShapeHint location: class net.sf.jasperreports.components.barcode4j.DataMatrixComponent C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\FourStateBarcodeComponent.java:[76,29] cannot find symbol symbol : class ChecksumMode location: class net.sf.jasperreports.components.barcode4j.FourStateBarcodeComponent C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\UPCAComponent.java:[56,29] cannot find symbol symbol : class ChecksumMode location: class net.sf.jasperreports.components.barcode4j.UPCAComponent C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\UPCEComponent.java:[56,29] cannot find symbol symbol : class ChecksumMode location: class net.sf.jasperreports.components.barcode4j.UPCEComponent C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\EAN13Component.java:[56,29] cannot find symbol symbol : class ChecksumMode location: class net.sf.jasperreports.components.barcode4j.EAN13Component C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\EAN8Component.java:[56,29] cannot find symbol symbol : class ChecksumMode location: class net.sf.jasperreports.components.barcode4j.EAN8Component C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\Interleaved2Of5Component.java:[60,29] cannot find symbol symbol : class ChecksumMode location: class net.sf.jasperreports.components.barcode4j.Interleaved2Of5Component C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\data\JRHibernateAbstractDataSource.java:[36,25] package org.hibernate.type does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[49,20] package org.hibernate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[50,20] package org.hibernate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[51,20] package org.hibernate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[52,20] package org.hibernate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[53,20] package org.hibernate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[54,25] package org.hibernate.type does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\data\JRHibernateAbstractDataSource.java:[173,38] cannot find symbol symbol : class Type location: class net.sf.jasperreports.engine.data.JRHibernateAbstractDataSource C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[66,35] cannot find symbol symbol : class Type location: class net.sf.jasperreports.engine.query.JRHibernateQueryExecuter C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[89,9] cannot find symbol symbol : class Session location: class net.sf.jasperreports.engine.query.JRHibernateQueryExecuter C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[90,9] cannot find symbol symbol : class Query location: class net.sf.jasperreports.engine.query.JRHibernateQueryExecuter C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[92,9] cannot find symbol symbol : class ScrollableResults location: class net.sf.jasperreports.engine.query.JRHibernateQueryExecuter C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[359,8] cannot find symbol symbol : class Type location: class net.sf.jasperreports.engine.query.JRHibernateQueryExecuter C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\query\JRHibernateQueryExecuter.java:[474,8] cannot find symbol symbol : class ScrollableResults location: class net.sf.jasperreports.engine.query.JRHibernateQueryExecuter C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barbecue\BarbecueFillComponent.java:[40,31] package net.sourceforge.barbecue does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[38,27] package org.apache.tools.ant does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[39,27] package org.apache.tools.ant does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[40,27] package org.apache.tools.ant does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[41,33] package org.apache.tools.ant.types does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[42,33] package org.apache.tools.ant.types does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[43,43] package org.apache.tools.ant.types.resources does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[44,32] package org.apache.tools.ant.util does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[45,32] package org.apache.tools.ant.util does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRBaseAntTask.java:[34,36] package org.apache.tools.ant.taskdefs does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRBaseAntTask.java:[41,35] cannot find symbol symbol: class MatchingTask public class JRBaseAntTask extends MatchingTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[74,9] cannot find symbol symbol : class Path location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[76,9] cannot find symbol symbol : class Path location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[86,23] cannot find symbol symbol : class Path location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[104,8] cannot find symbol symbol : class Path location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[131,8] cannot find symbol symbol : class Path location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[145,30] cannot find symbol symbol : class BuildException location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[183,41] cannot find symbol symbol : class BuildException location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[211,33] cannot find symbol symbol : class BuildException location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\ant\JRAntXmlExportTask.java:[276,32] cannot find symbol symbol : class BuildException location: class net.sf.jasperreports.ant.JRAntXmlExportTask C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\xml\TransformedPropertyRule.java:[27,34] package org.apache.commons.digester does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\xml\TransformedPropertyRule.java:[37,54] cannot find symbol symbol: class Rule public abstract class TransformedPropertyRule extends Rule C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\data\mondrian\MondrianDataAdapterService.java:[29,20] package mondrian.olap does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\data\mondrian\MondrianDataAdapterService.java:[30,20] package mondrian.olap does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\data\mondrian\MondrianDataAdapterService.java:[31,20] package mondrian.olap does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\data\mondrian\MondrianDataAdapterService.java:[45,9] cannot find symbol symbol : class Connection location: class net.sf.jasperreports.data.mondrian.MondrianDataAdapterService C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\data\JRXlsDataSource.java:[40,10] package jxl does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\data\JRXlsDataSource.java:[41,10] package jxl does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\data\JRXlsDataSource.java:[42,10] package jxl does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\data\JRXlsDataSource.java:[43,20] package jxl.read.biff does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\data\JRXlsDataSource.java:[66,9] cannot find symbol symbol : class Workbook location: class net.sf.jasperreports.engine.data.JRXlsDataSource C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\engine\data\JRXlsDataSource.java:[83,24] cannot find symbol symbol : class Workbook location: class net.sf.jasperreports.engine.data.JRXlsDataSource C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\olap\xmla\JRXmlaMember.java:[26,20] package mondrian.olap does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\olap\result\JROlapMember.java:[26,20] package mondrian.olap does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\olap\xmla\JRXmlaMember.java:[89,8] cannot find symbol symbol : class Member location: class net.sf.jasperreports.olap.xmla.JRXmlaMember C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\olap\result\JROlapMember.java:[46,1] cannot find symbol symbol : class Member location: interface net.sf.jasperreports.olap.result.JROlapMember C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\web\actions\AbstractAction.java:[43,36] package org.codehaus.jackson.annotate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\web\actions\AbstractAction.java:[49,1] cannot find symbol symbol: class JsonTypeInfo @JsonTypeInfo(use=JsonTypeInfo.Id.NAME, include=JsonTypeInfo.As.PROPERTY, property="actionName") C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[32,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[33,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[34,29] package org.krysalis.barcode4j does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[35,34] package org.krysalis.barcode4j.impl does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[36,42] package org.krysalis.barcode4j.impl.codabar does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[37,42] package org.krysalis.barcode4j.impl.code128 does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[38,42] package org.krysalis.barcode4j.impl.code128 does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[39,41] package org.krysalis.barcode4j.impl.code39 does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[40,45] package org.krysalis.barcode4j.impl.datamatrix does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[41,45] package org.krysalis.barcode4j.impl.datamatrix does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[42,44] package org.krysalis.barcode4j.impl.fourstate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[43,44] package org.krysalis.barcode4j.impl.fourstate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[44,44] package org.krysalis.barcode4j.impl.fourstate does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[45,42] package org.krysalis.barcode4j.impl.int2of5 does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[46,41] package org.krysalis.barcode4j.impl.pdf417 does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[47,42] package org.krysalis.barcode4j.impl.postnet does not exist C:\Development\global_stock_record\test\java\Turtle\src\main\java\net\sf\jasperreports\components\barcode4j\AbstractBarcodeEvaluator.java:[48,41] package org.krysalis.barcode4j.impl.upcean does not exist [INFO] ------------------------------------------------------------------------ [INFO] For more information, run Maven with the -e switch [INFO] ------------------------------------------------------------------------ [INFO] Total time: 17 seconds [INFO] Finished at: Fri Dec 07 11:46:28 EST 2012 [INFO] Final Memory: 27M/63M [INFO] ------------------------------------------------------------------------

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  • SINGLE SIGN ON SECURITY THREAT! FACEBOOK access_token broadcast in the open/clear

    - by MOKANA
    Subsequent to my posting there was a remark made that this was not really a question but I thought I did indeed postulate one. So that there is no ambiquity here is the question with a lead in: Since there is no data sent from Facebook during the Canvas Load process that is not at some point divulged, including the access_token, session and other data that could uniquely identify a user, does any one see any other way other than adding one more layer, i.e., a password, sent over the wire via HTTPS along with the access_toekn, that will insure unique untampered with security by the user? Using Wireshark I captured the local broadcast while loading my Canvas Application page. I was hugely surprised to see the access_token broadcast in the open, viewable for any one to see. This access_token is appended to any https call to the Facebook OpenGraph API. Using facebook as a single click log on has now raised huge concerns for me. It is stored in a session object in memory and the cookie is cleared upon app termination and after reviewing the FB.Init calls I saw a lot of HTTPS calls so I assumed the access_token was always encrypted. But last night I saw in the status bar a call from what was simply an http call that included the App ID so I felt I should sniff the Application Canvas load sequence. Today I did sniff the broadcast and in the attached image you can see that there are http calls with the access_token being broadcast in the open and clear for anyone to gain access to. Am I missing something, is what I am seeing and my interpretation really correct. If any one can sniff and get the access_token they can theorically make calls to the Graph API via https, even though the call back would still need to be the site established in Facebook's application set up. But what is truly a security threat is anyone using the access_token for access to their own site. I do not see the value of a single sign on via Facebook if the only thing that was established as secure was the access_token - becuase for what I can see it clearly is not secure. Access tokens that never have an expire date do not change. Access_tokens are different for every user, to access to another site could be held tight to just a single user, but compromising even a single user's data is unacceptable. http://www.creatingstory.com/images/InTheOpen.png Went back and did more research on this: FINDINGS: Went back an re ran the canvas application to verify that it was not any of my code that was not broadcasting. In this call: HTTP GET /connect.php/en_US/js/CacheData HTTP/1.1 The USER ID is clearly visible in the cookie. So USER_ID's are fully visible, but they are already. Anyone can go to pretty much any ones page and hover over the image and see the USER ID. So no big threat. APP_ID are also easily obtainable - but . . . http://www.creatingstory.com/images/InTheOpen2.png The above file clearly shows the FULL ACCESS TOKEN clearly in the OPEN via a Facebook initiated call. Am I wrong. TELL ME I AM WRONG because I want to be wrong about this. I have since reset my app secret so I am showing the real sniff of the Canvas Page being loaded. Additional data 02/20/2011: @ifaour - I appreciate the time you took to compile your response. I am pretty familiar with the OAuth process and have a pretty solid understanding of the signed_request unpacking and utilization of the access_token. I perform a substantial amount of my processing on the server and my Facebook server side flows are all complete and function without any flaw that I know of. The application secret is secure and never passed to the front end application and is also changed regularly. I am being as fanatical about security as I can be, knowing there is so much I don’t know that could come back and bite me. Two huge access_token issues: The issues concern the possible utilization of the access_token from the USER AGENT (browser). During the FB.INIT() process of the Facebook JavaScript SDK, a cookie is created as well as an object in memory called a session object. This object, along with the cookie contain the access_token, session, a secret, and uid and status of the connection. The session object is structured such that is supports both the new OAuth and the legacy flows. With OAuth, the access_token and status are pretty much al that is used in the session object. The first issue is that the access_token is used to make HTTPS calls to the GRAPH API. If you had the access_token, you could do this from any browser: https://graph.facebook.com/220439?access_token=... and it will return a ton of information about the user. So any one with the access token can gain access to a Facebook account. You can also make additional calls to any info the user has granted access to the application tied to the access_token. At first I thought that a call into the GRAPH had to have a Callback to the URL established in the App Setup, but I tested it as mentioned below and it will return info back right into the browser. Adding that callback feature would be a good idea I think, tightens things up a bit. The second issue is utilization of some unique private secured data that identifies the user to the third party data base, i.e., like in my case, I would use a single sign on to populate user information into my database using this unique secured data item (i.e., access_token which contains the APP ID, the USER ID, and a hashed with secret sequence). None of this is a problem on the server side. You get a signed_request, you unpack it with secret, make HTTPS calls, get HTTPS responses back. When a user has information entered via the USER AGENT(browser) that must be stored via a POST, this unique secured data element would be sent via HTTPS such that they are validated prior to data base insertion. However, If there is NO secured piece of unique data that is supplied via the single sign on process, then there is no way to guarantee unauthorized access. The access_token is the one piece of data that is utilized by Facebook to make the HTTPS calls into the GRAPH API. it is considered unique in regards to BOTH the USER and the APPLICATION and is initially secure via the signed_request packaging. If however, it is subsequently transmitted in the clear and if I can sniff the wire and obtain the access_token, then I can pretend to be the application and gain the information they have authorized the application to see. I tried the above example from a Safari and IE browser and it returned all of my information to me in the browser. In conclusion, the access_token is part of the signed_request and that is how the application initially obtains it. After OAuth authentication and authorization, i.e., the USER has logged into Facebook and then runs your app, the access_token is stored as mentioned above and I have sniffed it such that I see it stored in a Cookie that is transmitted over the wire, resulting in there being NO UNIQUE SECURED IDENTIFIABLE piece of information that can be used to support interaction with the database, or in other words, unless there were one more piece of secure data sent along with the access_token to my database, i.e., a password, I would not be able to discern if it is a legitimate call. Luckily I utilized secure AJAX via POST and the call has to come from the same domain, but I am sure there is a way to hijack that. I am totally open to any ideas on this topic on how to uniquely identify my USERS other than adding another layer (password) via this single sign on process or if someone would just share with me that I read and analyzed my data incorrectly and that the access_token is always secure over the wire. Mahalo nui loa in advance.

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  • More than 100,000 articles !

    - by developerit
    In one month, we already got more than 100,000, and we continue to crawl! We plan on hitting 250,000 total articles next month. Due to the large amount of data we are gathering, we are planning on updating our SQL stored procedure to improve performance. We may be migrating to SQL Server 2008 Entreprise, as we are currently running on SQL Server 2005 Express Edition… We are at 400 Mb of data, getting more and more close to the 2 Gb limit. Stay tune for more info and browse daily fresh articles about web development.

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  • The OLE DB provider "SQLNCLI10.1" has not been registered.; 42000.

    - by lankylad
    I have a SQL Server 2008 Analysis Services Project. In the Data Source View I have a Named Query which references a single Data Source containing three tables. The Project processes successfully and the cube can be browsed. I recently added a second Data Source to the Data Source View and linked a table to the original Named Query. When I try to process the project, I get the message: OLE DB error: OLE DB or ODBC error: The OLE DB provider "SQLNCLI10.1" has not been registered.; 42000. The Connection String for both Data Sources uses SQLNCLI10.1

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  • Using JSON.NET for dynamic JSON parsing

    - by Rick Strahl
    With the release of ASP.NET Web API as part of .NET 4.5 and MVC 4.0, JSON.NET has effectively pushed out the .NET native serializers to become the default serializer for Web API. JSON.NET is vastly more flexible than the built in DataContractJsonSerializer or the older JavaScript serializer. The DataContractSerializer in particular has been very problematic in the past because it can't deal with untyped objects for serialization - like values of type object, or anonymous types which are quite common these days. The JavaScript Serializer that came before it actually does support non-typed objects for serialization but it can't do anything with untyped data coming in from JavaScript and it's overall model of extensibility was pretty limited (JavaScript Serializer is what MVC uses for JSON responses). JSON.NET provides a robust JSON serializer that has both high level and low level components, supports binary JSON, JSON contracts, Xml to JSON conversion, LINQ to JSON and many, many more features than either of the built in serializers. ASP.NET Web API now uses JSON.NET as its default serializer and is now pulled in as a NuGet dependency into Web API projects, which is great. Dynamic JSON Parsing One of the features that I think is getting ever more important is the ability to serialize and deserialize arbitrary JSON content dynamically - that is without mapping the JSON captured directly into a .NET type as DataContractSerializer or the JavaScript Serializers do. Sometimes it isn't possible to map types due to the differences in languages (think collections, dictionaries etc), and other times you simply don't have the structures in place or don't want to create them to actually import the data. If this topic sounds familiar - you're right! I wrote about dynamic JSON parsing a few months back before JSON.NET was added to Web API and when Web API and the System.Net HttpClient libraries included the System.Json classes like JsonObject and JsonArray. With the inclusion of JSON.NET in Web API these classes are now obsolete and didn't ship with Web API or the client libraries. I re-linked my original post to this one. In this post I'll discus JToken, JObject and JArray which are the dynamic JSON objects that make it very easy to create and retrieve JSON content on the fly without underlying types. Why Dynamic JSON? So, why Dynamic JSON parsing rather than strongly typed parsing? Since applications are interacting more and more with third party services it becomes ever more important to have easy access to those services with easy JSON parsing. Sometimes it just makes lot of sense to pull just a small amount of data out of large JSON document received from a service, because the third party service isn't directly related to your application's logic most of the time - and it makes little sense to map the entire service structure in your application. For example, recently I worked with the Google Maps Places API to return information about businesses close to me (or rather the app's) location. The Google API returns a ton of information that my application had no interest in - all I needed was few values out of the data. Dynamic JSON parsing makes it possible to map this data, without having to map the entire API to a C# data structure. Instead I could pull out the three or four values I needed from the API and directly store it on my business entities that needed to receive the data - no need to map the entire Maps API structure. Getting JSON.NET The easiest way to use JSON.NET is to grab it via NuGet and add it as a reference to your project. You can add it to your project with: PM> Install-Package Newtonsoft.Json From the Package Manager Console or by using Manage NuGet Packages in your project References. As mentioned if you're using ASP.NET Web API or MVC 4 JSON.NET will be automatically added to your project. Alternately you can also go to the CodePlex site and download the latest version including source code: http://json.codeplex.com/ Creating JSON on the fly with JObject and JArray Let's start with creating some JSON on the fly. It's super easy to create a dynamic object structure with any of the JToken derived JSON.NET objects. The most common JToken derived classes you are likely to use are JObject and JArray. JToken implements IDynamicMetaProvider and so uses the dynamic  keyword extensively to make it intuitive to create object structures and turn them into JSON via dynamic object syntax. Here's an example of creating a music album structure with child songs using JObject for the base object and songs and JArray for the actual collection of songs:[TestMethod] public void JObjectOutputTest() { // strong typed instance var jsonObject = new JObject(); // you can explicitly add values here using class interface jsonObject.Add("Entered", DateTime.Now); // or cast to dynamic to dynamically add/read properties dynamic album = jsonObject; album.AlbumName = "Dirty Deeds Done Dirt Cheap"; album.Artist = "AC/DC"; album.YearReleased = 1976; album.Songs = new JArray() as dynamic; dynamic song = new JObject(); song.SongName = "Dirty Deeds Done Dirt Cheap"; song.SongLength = "4:11"; album.Songs.Add(song); song = new JObject(); song.SongName = "Love at First Feel"; song.SongLength = "3:10"; album.Songs.Add(song); Console.WriteLine(album.ToString()); } This produces a complete JSON structure: { "Entered": "2012-08-18T13:26:37.7137482-10:00", "AlbumName": "Dirty Deeds Done Dirt Cheap", "Artist": "AC/DC", "YearReleased": 1976, "Songs": [ { "SongName": "Dirty Deeds Done Dirt Cheap", "SongLength": "4:11" }, { "SongName": "Love at First Feel", "SongLength": "3:10" } ] } Notice that JSON.NET does a nice job formatting the JSON, so it's easy to read and paste into blog posts :-). JSON.NET includes a bunch of configuration options that control how JSON is generated. Typically the defaults are just fine, but you can override with the JsonSettings object for most operations. The important thing about this code is that there's no explicit type used for holding the values to serialize to JSON. Rather the JSON.NET objects are the containers that receive the data as I build up my JSON structure dynamically, simply by adding properties. This means this code can be entirely driven at runtime without compile time restraints of structure for the JSON output. Here I use JObject to create a album 'object' and immediately cast it to dynamic. JObject() is kind of similar in behavior to ExpandoObject in that it allows you to add properties by simply assigning to them. Internally, JObject values are stored in pseudo collections of key value pairs that are exposed as properties through the IDynamicMetaObject interface exposed in JSON.NET's JToken base class. For objects the syntax is very clean - you add simple typed values as properties. For objects and arrays you have to explicitly create new JObject or JArray, cast them to dynamic and then add properties and items to them. Always remember though these values are dynamic - which means no Intellisense and no compiler type checking. It's up to you to ensure that the names and values you create are accessed consistently and without typos in your code. Note that you can also access the JObject instance directly (not as dynamic) and get access to the underlying JObject type. This means you can assign properties by string, which can be useful for fully data driven JSON generation from other structures. Below you can see both styles of access next to each other:// strong type instance var jsonObject = new JObject(); // you can explicitly add values here jsonObject.Add("Entered", DateTime.Now); // expando style instance you can just 'use' properties dynamic album = jsonObject; album.AlbumName = "Dirty Deeds Done Dirt Cheap"; JContainer (the base class for JObject and JArray) is a collection so you can also iterate over the properties at runtime easily:foreach (var item in jsonObject) { Console.WriteLine(item.Key + " " + item.Value.ToString()); } The functionality of the JSON objects are very similar to .NET's ExpandObject and if you used it before, you're already familiar with how the dynamic interfaces to the JSON objects works. Importing JSON with JObject.Parse() and JArray.Parse() The JValue structure supports importing JSON via the Parse() and Load() methods which can read JSON data from a string or various streams respectively. Essentially JValue includes the core JSON parsing to turn a JSON string into a collection of JsonValue objects that can be then referenced using familiar dynamic object syntax. Here's a simple example:public void JValueParsingTest() { var jsonString = @"{""Name"":""Rick"",""Company"":""West Wind"", ""Entered"":""2012-03-16T00:03:33.245-10:00""}"; dynamic json = JValue.Parse(jsonString); // values require casting string name = json.Name; string company = json.Company; DateTime entered = json.Entered; Assert.AreEqual(name, "Rick"); Assert.AreEqual(company, "West Wind"); } The JSON string represents an object with three properties which is parsed into a JObject class and cast to dynamic. Once cast to dynamic I can then go ahead and access the object using familiar object syntax. Note that the actual values - json.Name, json.Company, json.Entered - are actually of type JToken and I have to cast them to their appropriate types first before I can do type comparisons as in the Asserts at the end of the test method. This is required because of the way that dynamic types work which can't determine the type based on the method signature of the Assert.AreEqual(object,object) method. I have to either assign the dynamic value to a variable as I did above, or explicitly cast ( (string) json.Name) in the actual method call. The JSON structure can be much more complex than this simple example. Here's another example of an array of albums serialized to JSON and then parsed through with JsonValue():[TestMethod] public void JsonArrayParsingTest() { var jsonString = @"[ { ""Id"": ""b3ec4e5c"", ""AlbumName"": ""Dirty Deeds Done Dirt Cheap"", ""Artist"": ""AC/DC"", ""YearReleased"": 1976, ""Entered"": ""2012-03-16T00:13:12.2810521-10:00"", ""AlbumImageUrl"": ""http://ecx.images-amazon.com/images/I/61kTaH-uZBL._AA115_.jpg"", ""AmazonUrl"": ""http://www.amazon.com/gp/product/…ASIN=B00008BXJ4"", ""Songs"": [ { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Dirty Deeds Done Dirt Cheap"", ""SongLength"": ""4:11"" }, { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Love at First Feel"", ""SongLength"": ""3:10"" }, { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Big Balls"", ""SongLength"": ""2:38"" } ] }, { ""Id"": ""7b919432"", ""AlbumName"": ""End of the Silence"", ""Artist"": ""Henry Rollins Band"", ""YearReleased"": 1992, ""Entered"": ""2012-03-16T00:13:12.2800521-10:00"", ""AlbumImageUrl"": ""http://ecx.images-amazon.com/images/I/51FO3rb1tuL._SL160_AA160_.jpg"", ""AmazonUrl"": ""http://www.amazon.com/End-Silence-Rollins-Band/dp/B0000040OX/ref=sr_1_5?ie=UTF8&qid=1302232195&sr=8-5"", ""Songs"": [ { ""AlbumId"": ""7b919432"", ""SongName"": ""Low Self Opinion"", ""SongLength"": ""5:24"" }, { ""AlbumId"": ""7b919432"", ""SongName"": ""Grip"", ""SongLength"": ""4:51"" } ] } ]"; JArray jsonVal = JArray.Parse(jsonString) as JArray; dynamic albums = jsonVal; foreach (dynamic album in albums) { Console.WriteLine(album.AlbumName + " (" + album.YearReleased.ToString() + ")"); foreach (dynamic song in album.Songs) { Console.WriteLine("\t" + song.SongName); } } Console.WriteLine(albums[0].AlbumName); Console.WriteLine(albums[0].Songs[1].SongName); } JObject and JArray in ASP.NET Web API Of course these types also work in ASP.NET Web API controller methods. If you want you can accept parameters using these object or return them back to the server. The following contrived example receives dynamic JSON input, and then creates a new dynamic JSON object and returns it based on data from the first:[HttpPost] public JObject PostAlbumJObject(JObject jAlbum) { // dynamic input from inbound JSON dynamic album = jAlbum; // create a new JSON object to write out dynamic newAlbum = new JObject(); // Create properties on the new instance // with values from the first newAlbum.AlbumName = album.AlbumName + " New"; newAlbum.NewProperty = "something new"; newAlbum.Songs = new JArray(); foreach (dynamic song in album.Songs) { song.SongName = song.SongName + " New"; newAlbum.Songs.Add(song); } return newAlbum; } The raw POST request to the server looks something like this: POST http://localhost/aspnetwebapi/samples/PostAlbumJObject HTTP/1.1User-Agent: FiddlerContent-type: application/jsonHost: localhostContent-Length: 88 {AlbumName: "Dirty Deeds",Songs:[ { SongName: "Problem Child"},{ SongName: "Squealer"}]} and the output that comes back looks like this: {  "AlbumName": "Dirty Deeds New",  "NewProperty": "something new",  "Songs": [    {      "SongName": "Problem Child New"    },    {      "SongName": "Squealer New"    }  ]} The original values are echoed back with something extra appended to demonstrate that we're working with a new object. When you receive or return a JObject, JValue, JToken or JArray instance in a Web API method, Web API ignores normal content negotiation and assumes your content is going to be received and returned as JSON, so effectively the parameter and result type explicitly determines the input and output format which is nice. Dynamic to Strong Type Mapping You can also map JObject and JArray instances to a strongly typed object, so you can mix dynamic and static typing in the same piece of code. Using the 2 Album jsonString shown earlier, the code below takes an array of albums and picks out only a single album and casts that album to a static Album instance.[TestMethod] public void JsonParseToStrongTypeTest() { JArray albums = JArray.Parse(jsonString) as JArray; // pick out one album JObject jalbum = albums[0] as JObject; // Copy to a static Album instance Album album = jalbum.ToObject<Album>(); Assert.IsNotNull(album); Assert.AreEqual(album.AlbumName,jalbum.Value<string>("AlbumName")); Assert.IsTrue(album.Songs.Count > 0); } This is pretty damn useful for the scenario I mentioned earlier - you can read a large chunk of JSON and dynamically walk the property hierarchy down to the item you want to access, and then either access the specific item dynamically (as shown earlier) or map a part of the JSON to a strongly typed object. That's very powerful if you think about it - it leaves you in total control to decide what's dynamic and what's static. Strongly typed JSON Parsing With all this talk of dynamic let's not forget that JSON.NET of course also does strongly typed serialization which is drop dead easy. Here's a simple example on how to serialize and deserialize an object with JSON.NET:[TestMethod] public void StronglyTypedSerializationTest() { // Demonstrate deserialization from a raw string var album = new Album() { AlbumName = "Dirty Deeds Done Dirt Cheap", Artist = "AC/DC", Entered = DateTime.Now, YearReleased = 1976, Songs = new List<Song>() { new Song() { SongName = "Dirty Deeds Done Dirt Cheap", SongLength = "4:11" }, new Song() { SongName = "Love at First Feel", SongLength = "3:10" } } }; // serialize to string string json2 = JsonConvert.SerializeObject(album,Formatting.Indented); Console.WriteLine(json2); // make sure we can serialize back var album2 = JsonConvert.DeserializeObject<Album>(json2); Assert.IsNotNull(album2); Assert.IsTrue(album2.AlbumName == "Dirty Deeds Done Dirt Cheap"); Assert.IsTrue(album2.Songs.Count == 2); } JsonConvert is a high level static class that wraps lower level functionality, but you can also use the JsonSerializer class, which allows you to serialize/parse to and from streams. It's a little more work, but gives you a bit more control. The functionality available is easy to discover with Intellisense, and that's good because there's not a lot in the way of documentation that's actually useful. Summary JSON.NET is a pretty complete JSON implementation with lots of different choices for JSON parsing from dynamic parsing to static serialization, to complex querying of JSON objects using LINQ. It's good to see this open source library getting integrated into .NET, and pushing out the old and tired stock .NET parsers so that we finally have a bit more flexibility - and extensibility - in our JSON parsing. Good to go! Resources Sample Test Project http://json.codeplex.com/© Rick Strahl, West Wind Technologies, 2005-2012Posted in .NET  Web Api  AJAX   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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  • Understanding and Controlling Parallel Query Processing in SQL Server

    Data warehousing and general reporting applications tend to be CPU intensive because they need to read and process a large number of rows. To facilitate quick data processing for queries that touch a large amount of data, Microsoft SQL Server exploits the power of multiple logical processors to provide parallel query processing operations such as parallel scans. Through extensive testing, we have learned that, for most large queries that are executed in a parallel fashion, SQL Server can deliver linear or nearly linear response time speedup as the number of logical processors increases. However, some queries in high parallelism scenarios perform suboptimally. There are also some parallelism issues that can occur in a multi-user parallel query workload. This white paper describes parallel performance problems you might encounter when you run such queries and workloads, and it explains why these issues occur. In addition, it presents how data warehouse developers can detect these issues, and how they can work around them or mitigate them.

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  • Using jQuery, CKEditor, AJAX in ASP.NET MVC 2

    - by Ray Linder
    After banging my head for days on a “A potentially dangerous Request.Form value was detected" issue when post (ajax-ing) a form in ASP.NET MVC 2 on .NET 4.0 framework using jQuery and CKEditor, I found that when you use the following: Code Snippet $.ajax({     url: '/TheArea/Root/Add',     type: 'POST',     data: $("#form0Add").serialize(),     dataType: 'json',     //contentType: 'application/json; charset=utf-8',     beforeSend: function ()     {         pageNotify("NotifyMsgContentDiv", "MsgDefaultDiv", '<img src="/Content/images/content/icons/busy.gif" /> Adding post, please wait...', 300, "", true);         $("#btnAddSubmit").val("Please wait...").addClass("button-disabled").attr("disabled", "disabled");     },     success: function (data)     {         $("#btnAddSubmit").val("Add New Post").removeClass("button-disabled").removeAttr('disabled');         redirectToUrl("/Exhibitions");     },     error: function ()     {         pageNotify("NotifyMsgContentDiv", "MsgErrorDiv", '<img src="/Content/images/content/icons/cross.png" /> Could not add post. Please try again or contact your web administrator.', 6000, "normal");         $("#btnAddSubmit").val("Add New Post").removeClass("button-disabled").removeAttr('disabled');     } }); Notice the following: Code Snippet data: $("#form0Add").serialize(), You may run into the “A potentially dangerous Request.Form value was detected" issue with this. One of the requirements was NOT to disable ValidateRequest (ValidateRequest=”false”). For this project (and any other project) I felt it wasn’t necessary to disable ValidateRequest. Note: I’ve search for alternatives for the posting issue and everyone and their mothers continually suggested to disable ValidateRequest. That bothers me – a LOT. So, disabling ValidateRequest is totally out of the question (and always will be).  So I thought to modify how the “data: “ gets serialized. the ajax data fix was simple, add a .html(). YES!!! IT WORKS!!! No more “potentially dangerous” issue, ajax form posts (and does it beautifully)! So if you’re using jQuery to $.ajax() a form with CKEditor, remember to do: Code Snippet data: $("#form0Add").serialize().html(), or bad things will happen. Also, don’t forget to set Code Snippet config.htmlEncodeOutput = true; for the CKEditor config.js file (or equivalent). Example: Code Snippet CKEDITOR.editorConfig = function( config ) {     // Define changes to default configuration here. For example:     // config.language = 'fr';     config.uiColor = '#ccddff';     config.width = 640;     config.ignoreEmptyParagraph = true;     config.resize_enabled = false;     config.skin = 'kama';     config.enterMode = CKEDITOR.ENTER_BR;       config.toolbar = 'MyToolbar';     config.toolbar_MyToolbar =     [         ['Bold', 'Italic', 'Underline'],         ['JustifyLeft', 'JustifyCenter', 'JustifyRight', 'JustifyBlock', 'Font', 'FontSize', 'TextColor', 'BGColor'],         ['BulletedList', 'NumberedList', '-', 'Outdent', 'Indent'],         '/',         ['Scayt', '-', 'Cut', 'Copy', 'Paste', 'Find'],         ['Undo', 'Redo'],         ['Link', 'Unlink', 'Anchor', 'Image', 'Flash', 'HorizontalRule'],         ['Table'],         ['Preview', 'Source']     ];     config.htmlEncodeOutput = true; }; Happy coding!!! Tags: jQuery ASP.NET MVC 2 ASP.NET 4.0 AJAX

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  • Introducing Oracle VM Server for SPARC

    - by Honglin Su
    As you are watching Oracle's Virtualization Strategy Webcast and exploring the great virtualization offerings of Oracle VM product line, I'd like to introduce Oracle VM Server for SPARC --  highly efficient, enterprise-class virtualization solution for Sun SPARC Enterprise Systems with Chip Multithreading (CMT) technology. Oracle VM Server for SPARC, previously called Sun Logical Domains, leverages the built-in SPARC hypervisor to subdivide supported platforms' resources (CPUs, memory, network, and storage) by creating partitions called logical (or virtual) domains. Each logical domain can run an independent operating system. Oracle VM Server for SPARC provides the flexibility to deploy multiple Oracle Solaris operating systems simultaneously on a single platform. Oracle VM Server also allows you to create up to 128 virtual servers on one system to take advantage of the massive thread scale offered by the CMT architecture. Oracle VM Server for SPARC integrates both the industry-leading CMT capability of the UltraSPARC T1, T2 and T2 Plus processors and the Oracle Solaris operating system. This combination helps to increase flexibility, isolate workload processing, and improve the potential for maximum server utilization. Oracle VM Server for SPARC delivers the following: Leading Price/Performance - The low-overhead architecture provides scalable performance under increasing workloads without additional license cost. This enables you to meet the most aggressive price/performance requirement Advanced RAS - Each logical domain is an entirely independent virtual machine with its own OS. It supports virtual disk mutipathing and failover as well as faster network failover with link-based IP multipathing (IPMP) support. Moreover, it's fully integrated with Solaris FMA (Fault Management Architecture), which enables predictive self healing. CPU Dynamic Resource Management (DRM) - Enable your resource management policy and domain workload to trigger the automatic addition and removal of CPUs. This ability helps you to better align with your IT and business priorities. Enhanced Domain Migrations - Perform domain migrations interactively and non-interactively to bring more flexibility to the management of your virtualized environment. Improve active domain migration performance by compressing memory transfers and taking advantage of cryptographic acceleration hardware. These methods provide faster migration for load balancing, power saving, and planned maintenance. Dynamic Crypto Control - Dynamically add and remove cryptographic units (aka MAU) to and from active domains. Also, migrate active domains that have cryptographic units. Physical-to-virtual (P2V) Conversion - Quickly convert an existing SPARC server running the Oracle Solaris 8, 9 or 10 OS into a virtualized Oracle Solaris 10 image. Use this image to facilitate OS migration into the virtualized environment. Virtual I/O Dynamic Reconfiguration (DR) - Add and remove virtual I/O services and devices without needing to reboot the system. CPU Power Management - Implement power saving by disabling each core on a Sun UltraSPARC T2 or T2 Plus processor that has all of its CPU threads idle. Advanced Network Configuration - Configure the following network features to obtain more flexible network configurations, higher performance, and scalability: Jumbo frames, VLANs, virtual switches for link aggregations, and network interface unit (NIU) hybrid I/O. Official Certification Based On Real-World Testing - Use Oracle VM Server for SPARC with the most sophisticated enterprise workloads under real-world conditions, including Oracle Real Application Clusters (RAC). Affordable, Full-Stack Enterprise Class Support - Obtain worldwide support from Oracle for the entire virtualization environment and workloads together. The support covers hardware, firmware, OS, virtualization, and the software stack. SPARC Server Virtualization Oracle offers a full portfolio of virtualization solutions to address your needs. SPARC is the leading platform to have the hard partitioning capability that provides the physical isolation needed to run independent operating systems. Many customers have already used Oracle Solaris Containers for application isolation. Oracle VM Server for SPARC provides another important feature with OS isolation. This gives you the flexibility to deploy multiple operating systems simultaneously on a single Sun SPARC T-Series server with finer granularity for computing resources.  For SPARC CMT processors, the natural level of granularity is an execution thread, not a time-sliced microsecond of execution resources. Each CPU thread can be treated as an independent virtual processor. The scheduler is naturally built into the CPU for lower overhead and higher performance. Your organizations can couple Oracle Solaris Containers and Oracle VM Server for SPARC with the breakthrough space and energy savings afforded by Sun SPARC Enterprise systems with CMT technology to deliver a more agile, responsive, and low-cost environment. Management with Oracle Enterprise Manager Ops Center The Oracle Enterprise Manager Ops Center Virtualization Management Pack provides full lifecycle management of virtual guests, including Oracle VM Server for SPARC and Oracle Solaris Containers. It helps you streamline operations and reduce downtime. Together, the Virtualization Management Pack and the Ops Center Provisioning and Patch Automation Pack provide an end-to-end management solution for physical and virtual systems through a single web-based console. This solution automates the lifecycle management of physical and virtual systems and is the most effective systems management solution for Oracle's Sun infrastructure. Ease of Deployment with Configuration Assistant The Oracle VM Server for SPARC Configuration Assistant can help you easily create logical domains. After gathering the configuration data, the Configuration Assistant determines the best way to create a deployment to suit your requirements. The Configuration Assistant is available as both a graphical user interface (GUI) and terminal-based tool. Oracle Solaris Cluster HA Support The Oracle Solaris Cluster HA for Oracle VM Server for SPARC data service provides a mechanism for orderly startup and shutdown, fault monitoring and automatic failover of the Oracle VM Server guest domain service. In addition, applications that run on a logical domain, as well as its resources and dependencies can be controlled and managed independently. These are managed as if they were running in a classical Solaris Cluster hardware node. Supported Systems Oracle VM Server for SPARC is supported on all Sun SPARC Enterprise Systems with CMT technology. UltraSPARC T2 Plus Systems ·   Sun SPARC Enterprise T5140 Server ·   Sun SPARC Enterprise T5240 Server ·   Sun SPARC Enterprise T5440 Server ·   Sun Netra T5440 Server ·   Sun Blade T6340 Server Module ·   Sun Netra T6340 Server Module UltraSPARC T2 Systems ·   Sun SPARC Enterprise T5120 Server ·   Sun SPARC Enterprise T5220 Server ·   Sun Netra T5220 Server ·   Sun Blade T6320 Server Module ·   Sun Netra CP3260 ATCA Blade Server Note that UltraSPARC T1 systems are supported on earlier versions of the software.Sun SPARC Enterprise Systems with CMT technology come with the right to use (RTU) of Oracle VM Server, and the software is pre-installed. If you have the systems under warranty or with support, you can download the software and system firmware as well as their updates. Oracle Premier Support for Systems provides fully-integrated support for your server hardware, firmware, OS, and virtualization software. Visit oracle.com/support for information about Oracle's support offerings for Sun systems. For more information about Oracle's virtualization offerings, visit oracle.com/virtualization.

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  • Adding Client Validation To DataAnnotations DataType Attribute

    - by srkirkland
    The System.ComponentModel.DataAnnotations namespace contains a validation attribute called DataTypeAttribute, which takes an enum specifying what data type the given property conforms to.  Here are a few quick examples: public class DataTypeEntity { [DataType(DataType.Date)] public DateTime DateTime { get; set; }   [DataType(DataType.EmailAddress)] public string EmailAddress { get; set; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This attribute comes in handy when using ASP.NET MVC, because the type you specify will determine what “template” MVC uses.  Thus, for the DateTime property if you create a partial in Views/[loc]/EditorTemplates/Date.ascx (or cshtml for razor), that view will be used to render the property when using any of the Html.EditorFor() methods. One thing that the DataType() validation attribute does not do is any actual validation.  To see this, let’s take a look at the EmailAddress property above.  It turns out that regardless of the value you provide, the entity will be considered valid: //valid new DataTypeEntity {EmailAddress = "Foo"}; .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Hmmm.  Since DataType() doesn’t validate, that leaves us with two options: (1) Create our own attributes for each datatype to validate, like [Date], or (2) add validation into the DataType attribute directly.  In this post, I will show you how to hookup client-side validation to the existing DataType() attribute for a desired type.  From there adding server-side validation would be a breeze and even writing a custom validation attribute would be simple (more on that in future posts). Validation All The Way Down Our goal will be to leave our DataTypeEntity class (from above) untouched, requiring no reference to System.Web.Mvc.  Then we will make an ASP.NET MVC project that allows us to create a new DataTypeEntity and hookup automatic client-side date validation using the suggested “out-of-the-box” jquery.validate bits that are included with ASP.NET MVC 3.  For simplicity I’m going to focus on the only DateTime field, but the concept is generally the same for any other DataType. Building a DataTypeAttribute Adapter To start we will need to build a new validation adapter that we can register using ASP.NET MVC’s DataAnnotationsModelValidatorProvider.RegisterAdapter() method.  This method takes two Type parameters; The first is the attribute we are looking to validate with and the second is an adapter that should subclass System.Web.Mvc.ModelValidator. Since we are extending DataAnnotations we can use the subclass of ModelValidator called DataAnnotationsModelValidator<>.  This takes a generic argument of type DataAnnotations.ValidationAttribute, which lucky for us means the DataTypeAttribute will fit in nicely. So starting from there and implementing the required constructor, we get: public class DataTypeAttributeAdapter : DataAnnotationsModelValidator<DataTypeAttribute> { public DataTypeAttributeAdapter(ModelMetadata metadata, ControllerContext context, DataTypeAttribute attribute) : base(metadata, context, attribute) { } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Now you have a full-fledged validation adapter, although it doesn’t do anything yet.  There are two methods you can override to add functionality, IEnumerable<ModelValidationResult> Validate(object container) and IEnumerable<ModelClientValidationRule> GetClientValidationRules().  Adding logic to the server-side Validate() method is pretty straightforward, and for this post I’m going to focus on GetClientValidationRules(). Adding a Client Validation Rule Adding client validation is now incredibly easy because jquery.validate is very powerful and already comes with a ton of validators (including date and regular expressions for our email example).  Teamed with the new unobtrusive validation javascript support we can make short work of our ModelClientValidationDateRule: public class ModelClientValidationDateRule : ModelClientValidationRule { public ModelClientValidationDateRule(string errorMessage) { ErrorMessage = errorMessage; ValidationType = "date"; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } If your validation has additional parameters you can the ValidationParameters IDictionary<string,object> to include them.  There is a little bit of conventions magic going on here, but the distilled version is that we are defining a “date” validation type, which will be included as html5 data-* attributes (specifically data-val-date).  Then jquery.validate.unobtrusive takes this attribute and basically passes it along to jquery.validate, which knows how to handle date validation. Finishing our DataTypeAttribute Adapter Now that we have a model client validation rule, we can return it in the GetClientValidationRules() method of our DataTypeAttributeAdapter created above.  Basically I want to say if DataType.Date was provided, then return the date rule with a given error message (using ValidationAttribute.FormatErrorMessage()).  The entire adapter is below: public class DataTypeAttributeAdapter : DataAnnotationsModelValidator<DataTypeAttribute> { public DataTypeAttributeAdapter(ModelMetadata metadata, ControllerContext context, DataTypeAttribute attribute) : base(metadata, context, attribute) { }   public override System.Collections.Generic.IEnumerable<ModelClientValidationRule> GetClientValidationRules() { if (Attribute.DataType == DataType.Date) { return new[] { new ModelClientValidationDateRule(Attribute.FormatErrorMessage(Metadata.GetDisplayName())) }; }   return base.GetClientValidationRules(); } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Putting it all together Now that we have an adapter for the DataTypeAttribute, we just need to tell ASP.NET MVC to use it.  The easiest way to do this is to use the built in DataAnnotationsModelValidatorProvider by calling RegisterAdapter() in your global.asax startup method. DataAnnotationsModelValidatorProvider.RegisterAdapter(typeof(DataTypeAttribute), typeof(DataTypeAttributeAdapter)); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Show and Tell Let’s see this in action using a clean ASP.NET MVC 3 project.  First make sure to reference the jquery, jquery.vaidate and jquery.validate.unobtrusive scripts that you will need for client validation. Next, let’s make a model class (note we are using the same built-in DataType() attribute that comes with System.ComponentModel.DataAnnotations). public class DataTypeEntity { [DataType(DataType.Date, ErrorMessage = "Please enter a valid date (ex: 2/14/2011)")] public DateTime DateTime { get; set; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Then we make a create page with a strongly-typed DataTypeEntity model, the form section is shown below (notice we are just using EditorForModel): @using (Html.BeginForm()) { @Html.ValidationSummary(true) <fieldset> <legend>Fields</legend>   @Html.EditorForModel()   <p> <input type="submit" value="Create" /> </p> </fieldset> } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } The final step is to register the adapter in our global.asax file: DataAnnotationsModelValidatorProvider.RegisterAdapter(typeof(DataTypeAttribute), typeof(DataTypeAttributeAdapter)); Now we are ready to run the page: Looking at the datetime field’s html, we see that our adapter added some data-* validation attributes: <input type="text" value="1/1/0001" name="DateTime" id="DateTime" data-val-required="The DateTime field is required." data-val-date="Please enter a valid date (ex: 2/14/2011)" data-val="true" class="text-box single-line valid"> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Here data-val-required was added automatically because DateTime is non-nullable, and data-val-date was added by our validation adapter.  Now if we try to add an invalid date: Our custom error message is displayed via client-side validation as soon as we tab out of the box.  If we didn’t include a custom validation message, the default DataTypeAttribute “The field {0} is invalid” would have been shown (of course we can change the default as well).  Note we did not specify server-side validation, but in this case we don’t have to because an invalid date will cause a server-side error during model binding. Conclusion I really like how easy it is to register new data annotations model validators, whether they are your own or, as in this post, supplements to existing validation attributes.  I’m still debating about whether adding the validation directly in the DataType attribute is the correct place to put it versus creating a dedicated “Date” validation attribute, but it’s nice to know either option is available and, as we’ve seen, simple to implement. I’m also working through the nascent stages of an open source project that will create validation attribute extensions to the existing data annotations providers using similar techniques as seen above (examples: Email, Url, EqualTo, Min, Max, CreditCard, etc).  Keep an eye on this blog and subscribe to my twitter feed (@srkirkland) if you are interested for announcements.

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  • EFMVC Migrated to .NET 4.5, Visual Studio 2012, ASP.NET MVC 4 and EF 5 Code First

    - by shiju
    I have just migrated my EFMVC app from .NET 4.0 and ASP.NET MVC 4 RC to .NET 4.5, ASP.NET MVC 4 RTM and Entity Framework 5 Code First. In this release, the EFMVC solution is built with Visual Studio 2012 RTM. The migration process was very smooth and did not made any major changes other than adding simple unit tests with NUnit and Moq. I will add more unit tests on later and will also modify the existing solution. Source Code You can download the source code from http://efmvc.codeplex.com/

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  • Database users in the Oracle Utilities Application Framework

    - by Anthony Shorten
    I mentioned the product database users fleetingly in the last blog post and they deserve a better mention. This applies to all versions of the Oracle Utilities Application Framework. The Oracle Utilities Application Framework uses up to three users initially as part of the base operations of the product. The type of database supported (the framework supports Oracle, IBM DB2 and Microsoft SQL Server) dictates the number of users used and their permissions. For publishing brevity I will outline what is available for the Oracle database and, in summary, mention where it differs for the other database supported. For Oracle database customers we ship three distinct database users: Administration User (SPLADM or CISADM by default) - This is the database user that actually owns the schema. This user is not used by the product to do any DML (Data Manipulation Language) SQL other than that is necessary for maintenance of the database. This database user performs all the DCL (Data Control Language) and DDL (Data Definition Language) against the database. It is typically reserved for Database Administration use only. Product Read Write User (SPLUSER or CISUSER by default) - This is the database user used by the product itself to execute DML (Data Manipulation Language) statements against the schema owned by the Administration user. This user has the appropriate read and write permission to objects within the schema owned by the Administration user. For databases such as DB2 and SQL Server we may not create this user but use other DCL (Data Control Language) statements and facilities to simulate this user. Product Read User (SPLREAD or CISREAD by default) - This is the database that has read only permission to the schema owned by the Administration user. It is used for reporting or any part of the product or interface that requires read permissions to the database (for example, products that have ConfigLab and Archiving use this user for remote access). For databases such as DB2 and SQL Server we may not create this user but use other DCL (Data Control Language) statements and facilities to simulate this user. You may notice the words by default in the list above. The values supplied with the installer are the default and can be changed to what the site standard or implementation wants to use (as long as they conform to the standards supported by the underlying database). You can even create multiples of each within the same database and pointing to same schema. To manage the permissions for the users, there is a utility provided with the installation (oragensec (Oracle), db2gensec (DB2) or msqlgensec (SQL Server)) that generates the security definitions for the above users. That can be executed a number of times for each schema to give users appropriate permissions. For example, it is possible to define more than one read/write User to access the database. This is a common technique used by implementations to have a different user per access mode (to separate online and batch). In fact you can also allocate additional security (such as resource profiles in Oracle) to limit the impact of specific users at the database. To facilitate users and permissions, in Oracle for example, we create a CISREAD role (read only role) and a CISUSER role (read write role) that can be allocated to the appropriate database user. When the security permissions utility, oragensec in this case, is executed it uses the role to determine the permissions. To give you a case study, my underpowered laptop has multiple installations on it of multiple products but I have one database. I create a different schema for each product and each version (with my own naming convention to help me manage the databases). I create individual users on each schema and run oragensec to maintain the permissions for each appropriately. It works fine as long I have setup the userids appropriately. This means: Creating the users with the appropriate roles. I use the common CISUSER and CISREAD role across versions and across Oracle Utilities Application Framework products. Just remember to associate the CISUSER role with the database user you want to use for read/write operations and the CISREAD role with the user you wish to use for the read only operations. The role is treated as a tag to indicate the oragensec utility which appropriate permissions to assign to the user. The utilities for the other database types essentially do the same, obviously using the technology available within those databases. Run oragensec against the read write user and read only user against the appropriate administration user (I will abbreviate the user to ADM user). This ensures the right permissions are allocated to the right users for the right products. To help me there, I use the same prefix on the user name for the same product. For example, my Oracle Utilities Application Framework V4 environment has the administration user set to FW4ADM and the associated FW4USER and FW4READ as the users for the product to use. For my MWM environment I used MWMADM for the administration user and MWMUSER and MWMREAD for my associated users. You get the picture. When I run oragensec (once for each ADM user), I know what other users to associate with it. Remember to rerun oragensec against the users if I run upgrades, service packs or database based single fixes. This assures that the users are in synchronization with the ADM user. As a side note, for those who do not understand the difference between DML, DCL and DDL: DDL (Data Definition Language) - These are SQL statements that define the database schema and the structures within. SQL Statements such as CREATE and DROP are examples of DDL SQL statements. DCL (Data Control Language) - These are the SQL statements that define the database level permissions to DDL maintained objects within the database. SQL Statements such as GRANT and REVOKE are examples of DCL SQL statements. DML (Database Manipulation Language) - These are SQL statements that alter the data within the tables. SQL Statements such as SELECT, INSERT, UPDATE and DELETE are examples of DML SQL statements. Hope this has clarified the database user support. Remember in Oracle Utilities Application Framework V4 we enhanced this by also supporting CLIENT_IDENTIFIER to allow the database to still use the administration user for the main processing but make the database session more traceable.

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  • The OLE DB provider "SQLNCLI10.1" has not been registered.; 42000

    - by lankylad
    I have a SQL Server 2008 Analysis Services Project. In the Data Source View I have a Named Query which references a single Data Source containing three tables. The Project processes successfully and the cube can be browsed. I recently added a second Data Source to the Data Source View and linked a table to the original Named Query. When I try to process the project, I get the message: OLE DB error: OLE DB or ODBC error: The OLE DB provider "SQLNCLI10.1" has not been registered.; 42000. The Connection String for both Data Sources uses SQLNCLI10.1

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  • Interesting things – Twitter annotations and your phone as a web server

    - by jamiet
    I overheard/read a couple of things today that really made me, data junkie that I am, take a step back and think, “Hmmm, yeah, that could be really interesting” and I wanted to make a note of them here so that (a) I could bring them to the attention of anyone that happens to read this and (b) I can maybe come back here in a few years and see if either of these have come to fruition. Your phone as a web server While listening to Jon Udell’s (twitter) “Interviews with Innovators Podcast” today in which he interviewed Herbert Van de Sompel (twitter) about his Momento project. During the interview Jon and Herbert made the following remarks: Jon: [some people] really had this vision of a web of servers, the notion that every node on the internet, every connected entity, is potentially a server and a client…we can see where we’re getting to a point where these endpoint devices we have in our pockets are going to be massively capable and it may be in the not too distant future that significant chunks of the web archive will be cached all over the place including on your own machine… Herbert: wasn’t it Opera who at one point turned your browser into a server? That really got my brain ticking. We all carry a mobile phone with us and therefore we all potentially carry a mobile web server with us as well and to my mind the only thing really stopping that from happening is the capabilities of the phone hardware, the capabilities of the network infrastructure and the will to just bloody do it. Certainly all the standards required for addressing a web server on a phone already exist (to this uninitiated observer DNS and IPv6 seem to solve that problem) so why not? I tweeted about the idea and Rory Street answered back with “why would you want a phone to be a web server?”: Its a fair question and one that I would like to try and answer. Mobile phones are increasingly becoming our window onto the world as we use them to upload messages to Twitter, record our location on FourSquare or interact with our friends on Facebook but in each of these cases some other service is acting as our intermediary; to see what I’m thinking you have to go via Twitter, to see where I am you have to go to FourSquare (I’m using ‘I’ liberally, I don’t actually use FourSquare before you ask). Why should this have to be the case? Why can’t that data be decentralised? Why can’t we be masters of our own data universe? If my phone acted as a web server then I could expose all of that information without needing those intermediary services. I see a time when we can pass around URLs such as the following: http://jamiesphone.net/location/current - Where is Jamie right now? http://jamiesphone.net/location/2010-04-21 – Where was Jamie on 21st April 2010? http://jamiesphone.net/thoughts/current – What’s on Jamie’s mind right now? http://jamiesphone.net/blog – What documents is Jamie sharing with me? http://jamiesphone.net/calendar/next7days – Where is Jamie planning to be over the next 7 days? and those URLs get served off of the phone in our pockets. If we govern that data then we can control who has access to it and (crucially) how long its available for. Want to wipe yourself off the face of the web? its pretty easy if you’re in control of all the data – just turn your phone off. None of this exists today but I look forward to a time when it does. Opera really were onto something last June when they announced Opera Unite (admittedly Unite only works because Opera provide an intermediary DNS-alike system – it isn’t totally decentralised). Opening up Twitter annotations Last week Twitter held their first developer conference called Chirp where they announced an upcoming new feature called ‘Twitter Annotations’; in short this will allow us to attach metadata to a Tweet thus enhancing the tweet itself. Think of it as a richer version of hashtags. To think of it another way Twitter are turning their data into a humongous Entity-Attribute-Value or triple-tuple store. That alone has huge implications both for the web and Twitter as a whole – the ability to enrich that 140 characters data and thus make it more useful is indeed compelling however today I stumbled upon a blog post from Eugene Mandel entitled Tweet Annotations – a Way to a Metadata Marketplace? where he proposed the idea of allowing tweets to have metadata added by people other than the person who tweeted the original tweet. This idea really fascinated me especially when I read some of the potential uses that Eugene and his commenters suggested. They included: Amazon could attach an ISBN to a tweet that mentions a book. Specialist clients apps for book lovers could be built up around this metadata. Advertisers could pay to place adverts in metadata. The revenue generated from those adverts could be shared with the tweeter or people who add the metadata. Granted, allowing anyone to add metadata to a tweet has the potential to create a spam problem the like of which we haven’t even envisaged but spam hasn’t halted the growth of the web and neither should it halt the growth of data annotations either. The original tweeter should of course be able to determine who can add metadata and whether it should be moderated. As Eugene says himself: Opening publishing tweet annotations to anyone will open the way to a marketplace of metadata where client developers, data mining companies and advertisers can add new meaning to Twitter and build innovative businesses. What Eugene and his followers did not mention is what I think is potentially the most fascinating use of opening up annotations. Google’s success today is built on their page rank algorithm that measures the validity of a web page by the number of incoming links to it and the page rank of the sites containing those links – its a system built on reputation. Twitter annotations could open up a new paradigm however – let’s call it People rank- where reputation can be measured by the metadata that people choose to apply to links and the websites containing those links. Its not hard to see why Google and Microsoft have paid big bucks to get access to the Twitter firehose! Neither of these features, phones as a web server or the ability to add annotations to other people’s tweets, exist today but I strongly believe that they could dramatically enhance the web as we know it today. I hope to look back on this blog post in a few years in the knowledge that these ideas have been put into place. @Jamiet Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Using linked servers, OPENROWSET and OPENQUERY

    - by BuckWoody
    SQL Server has a few mechanisms to reach out to another server (even another server type) and query data from within a Transact-SQL statement. Among them are a set of stored credentials and information (called a Linked Server), a statement that uses a linked server called called OPENQUERY, another called OPENROWSET, and one called OPENDATASOURCE. This post isn’t about those particular functions or statements – hit the links for more if you’re new to those topics. I’m actually more concerned about where I see these used than the particular method. In many cases, a Linked server isn’t another Relational Database Management System (RDMBS) like Oracle or DB2 (which is possible with a linked server), but another SQL Server. My concern is that linked servers are the new Data Transformation Services (DTS) from SQL Server 2000 – something that was designed for one purpose but which is being morphed into something much more. In the case of DTS, most of us turned that feature into a full-fledged job system. What was designed as a simple data import and export system has been pressed into service doing logic, routing and timing. And of course we all know how painful it was to move off of a complex DTS system onto SQL Server Integration Services. In the case of linked servers, what should be used as a method of running a simple query or two on another server where you have occasional connection or need a quick import of a small data set is morphing into a full federation strategy. In some cases I’ve seen a complex web of linked servers, and when credentials, names or anything else changes there are huge problems. Now don’t get me wrong – linked servers and other forms of distributing queries is a fantastic set of tools that we have to move data around. I’m just saying that when you start having lots of workarounds and when things get really complicated, you might want to step back a little and ask if there’s a better way. Are you able to tolerate some latency? Perhaps you’re able to use Service Broker. Would you like to be platform-independent on the data source? Perhaps a middle-tier might make more sense, abstracting the queries there and sending them to the proper server. Designed properly, I’ve seen these systems scale further and be more resilient than loading up on linked servers. Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Toorcon14

    - by danx
    Toorcon 2012 Information Security Conference San Diego, CA, http://www.toorcon.org/ Dan Anderson, October 2012 It's almost Halloween, and we all know what that means—yes, of course, it's time for another Toorcon Conference! Toorcon is an annual conference for people interested in computer security. This includes the whole range of hackers, computer hobbyists, professionals, security consultants, press, law enforcement, prosecutors, FBI, etc. We're at Toorcon 14—see earlier blogs for some of the previous Toorcon's I've attended (back to 2003). This year's "con" was held at the Westin on Broadway in downtown San Diego, California. The following are not necessarily my views—I'm just the messenger—although I could have misquoted or misparaphrased the speakers. Also, I only reviewed some of the talks, below, which I attended and interested me. MalAndroid—the Crux of Android Infections, Aditya K. Sood Programming Weird Machines with ELF Metadata, Rebecca "bx" Shapiro Privacy at the Handset: New FCC Rules?, Valkyrie Hacking Measured Boot and UEFI, Dan Griffin You Can't Buy Security: Building the Open Source InfoSec Program, Boris Sverdlik What Journalists Want: The Investigative Reporters' Perspective on Hacking, Dave Maas & Jason Leopold Accessibility and Security, Anna Shubina Stop Patching, for Stronger PCI Compliance, Adam Brand McAfee Secure & Trustmarks — a Hacker's Best Friend, Jay James & Shane MacDougall MalAndroid—the Crux of Android Infections Aditya K. Sood, IOActive, Michigan State PhD candidate Aditya talked about Android smartphone malware. There's a lot of old Android software out there—over 50% Gingerbread (2.3.x)—and most have unpatched vulnerabilities. Of 9 Android vulnerabilities, 8 have known exploits (such as the old Gingerbread Global Object Table exploit). Android protection includes sandboxing, security scanner, app permissions, and screened Android app market. The Android permission checker has fine-grain resource control, policy enforcement. Android static analysis also includes a static analysis app checker (bouncer), and a vulnerablity checker. What security problems does Android have? User-centric security, which depends on the user to grant permission and make smart decisions. But users don't care or think about malware (the're not aware, not paranoid). All they want is functionality, extensibility, mobility Android had no "proper" encryption before Android 3.0 No built-in protection against social engineering and web tricks Alternative Android app markets are unsafe. Simply visiting some markets can infect Android Aditya classified Android Malware types as: Type A—Apps. These interact with the Android app framework. For example, a fake Netflix app. Or Android Gold Dream (game), which uploads user files stealthy manner to a remote location. Type K—Kernel. Exploits underlying Linux libraries or kernel Type H—Hybrid. These use multiple layers (app framework, libraries, kernel). These are most commonly used by Android botnets, which are popular with Chinese botnet authors What are the threats from Android malware? These incude leak info (contacts), banking fraud, corporate network attacks, malware advertising, malware "Hackivism" (the promotion of social causes. For example, promiting specific leaders of the Tunisian or Iranian revolutions. Android malware is frequently "masquerated". That is, repackaged inside a legit app with malware. To avoid detection, the hidden malware is not unwrapped until runtime. The malware payload can be hidden in, for example, PNG files. Less common are Android bootkits—there's not many around. What they do is hijack the Android init framework—alteering system programs and daemons, then deletes itself. For example, the DKF Bootkit (China). Android App Problems: no code signing! all self-signed native code execution permission sandbox — all or none alternate market places no robust Android malware detection at network level delayed patch process Programming Weird Machines with ELF Metadata Rebecca "bx" Shapiro, Dartmouth College, NH https://github.com/bx/elf-bf-tools @bxsays on twitter Definitions. "ELF" is an executable file format used in linking and loading executables (on UNIX/Linux-class machines). "Weird machine" uses undocumented computation sources (I think of them as unintended virtual machines). Some examples of "weird machines" are those that: return to weird location, does SQL injection, corrupts the heap. Bx then talked about using ELF metadata as (an uintended) "weird machine". Some ELF background: A compiler takes source code and generates a ELF object file (hello.o). A static linker makes an ELF executable from the object file. A runtime linker and loader takes ELF executable and loads and relocates it in memory. The ELF file has symbols to relocate functions and variables. ELF has two relocation tables—one at link time and another one at loading time: .rela.dyn (link time) and .dynsym (dynamic table). GOT: Global Offset Table of addresses for dynamically-linked functions. PLT: Procedure Linkage Tables—works with GOT. The memory layout of a process (not the ELF file) is, in order: program (+ heap), dynamic libraries, libc, ld.so, stack (which includes the dynamic table loaded into memory) For ELF, the "weird machine" is found and exploited in the loader. ELF can be crafted for executing viruses, by tricking runtime into executing interpreted "code" in the ELF symbol table. One can inject parasitic "code" without modifying the actual ELF code portions. Think of the ELF symbol table as an "assembly language" interpreter. It has these elements: instructions: Add, move, jump if not 0 (jnz) Think of symbol table entries as "registers" symbol table value is "contents" immediate values are constants direct values are addresses (e.g., 0xdeadbeef) move instruction: is a relocation table entry add instruction: relocation table "addend" entry jnz instruction: takes multiple relocation table entries The ELF weird machine exploits the loader by relocating relocation table entries. The loader will go on forever until told to stop. It stores state on stack at "end" and uses IFUNC table entries (containing function pointer address). The ELF weird machine, called "Brainfu*k" (BF) has: 8 instructions: pointer inc, dec, inc indirect, dec indirect, jump forward, jump backward, print. Three registers - 3 registers Bx showed example BF source code that implemented a Turing machine printing "hello, world". More interesting was the next demo, where bx modified ping. Ping runs suid as root, but quickly drops privilege. BF modified the loader to disable the library function call dropping privilege, so it remained as root. Then BF modified the ping -t argument to execute the -t filename as root. It's best to show what this modified ping does with an example: $ whoami bx $ ping localhost -t backdoor.sh # executes backdoor $ whoami root $ The modified code increased from 285948 bytes to 290209 bytes. A BF tool compiles "executable" by modifying the symbol table in an existing ELF executable. The tool modifies .dynsym and .rela.dyn table, but not code or data. Privacy at the Handset: New FCC Rules? "Valkyrie" (Christie Dudley, Santa Clara Law JD candidate) Valkyrie talked about mobile handset privacy. Some background: Senator Franken (also a comedian) became alarmed about CarrierIQ, where the carriers track their customers. Franken asked the FCC to find out what obligations carriers think they have to protect privacy. The carriers' response was that they are doing just fine with self-regulation—no worries! Carriers need to collect data, such as missed calls, to maintain network quality. But carriers also sell data for marketing. Verizon sells customer data and enables this with a narrow privacy policy (only 1 month to opt out, with difficulties). The data sold is not individually identifiable and is aggregated. But Verizon recommends, as an aggregation workaround to "recollate" data to other databases to identify customers indirectly. The FCC has regulated telephone privacy since 1934 and mobile network privacy since 2007. Also, the carriers say mobile phone privacy is a FTC responsibility (not FCC). FTC is trying to improve mobile app privacy, but FTC has no authority over carrier / customer relationships. As a side note, Apple iPhones are unique as carriers have extra control over iPhones they don't have with other smartphones. As a result iPhones may be more regulated. Who are the consumer advocates? Everyone knows EFF, but EPIC (Electrnic Privacy Info Center), although more obsecure, is more relevant. What to do? Carriers must be accountable. Opt-in and opt-out at any time. Carriers need incentive to grant users control for those who want it, by holding them liable and responsible for breeches on their clock. Location information should be added current CPNI privacy protection, and require "Pen/trap" judicial order to obtain (and would still be a lower standard than 4th Amendment). Politics are on a pro-privacy swing now, with many senators and the Whitehouse. There will probably be new regulation soon, and enforcement will be a problem, but consumers will still have some benefit. Hacking Measured Boot and UEFI Dan Griffin, JWSecure, Inc., Seattle, @JWSdan Dan talked about hacking measured UEFI boot. First some terms: UEFI is a boot technology that is replacing BIOS (has whitelisting and blacklisting). UEFI protects devices against rootkits. TPM - hardware security device to store hashs and hardware-protected keys "secure boot" can control at firmware level what boot images can boot "measured boot" OS feature that tracks hashes (from BIOS, boot loader, krnel, early drivers). "remote attestation" allows remote validation and control based on policy on a remote attestation server. Microsoft pushing TPM (Windows 8 required), but Google is not. Intel TianoCore is the only open source for UEFI. Dan has Measured Boot Tool at http://mbt.codeplex.com/ with a demo where you can also view TPM data. TPM support already on enterprise-class machines. UEFI Weaknesses. UEFI toolkits are evolving rapidly, but UEFI has weaknesses: assume user is an ally trust TPM implicitly, and attached to computer hibernate file is unprotected (disk encryption protects against this) protection migrating from hardware to firmware delays in patching and whitelist updates will UEFI really be adopted by the mainstream (smartphone hardware support, bank support, apathetic consumer support) You Can't Buy Security: Building the Open Source InfoSec Program Boris Sverdlik, ISDPodcast.com co-host Boris talked about problems typical with current security audits. "IT Security" is an oxymoron—IT exists to enable buiness, uptime, utilization, reporting, but don't care about security—IT has conflict of interest. There's no Magic Bullet ("blinky box"), no one-size-fits-all solution (e.g., Intrusion Detection Systems (IDSs)). Regulations don't make you secure. The cloud is not secure (because of shared data and admin access). Defense and pen testing is not sexy. Auditors are not solution (security not a checklist)—what's needed is experience and adaptability—need soft skills. Step 1: First thing is to Google and learn the company end-to-end before you start. Get to know the management team (not IT team), meet as many people as you can. Don't use arbitrary values such as CISSP scores. Quantitive risk assessment is a myth (e.g. AV*EF-SLE). Learn different Business Units, legal/regulatory obligations, learn the business and where the money is made, verify company is protected from script kiddies (easy), learn sensitive information (IP, internal use only), and start with low-hanging fruit (customer service reps and social engineering). Step 2: Policies. Keep policies short and relevant. Generic SANS "security" boilerplate policies don't make sense and are not followed. Focus on acceptable use, data usage, communications, physical security. Step 3: Implementation: keep it simple stupid. Open source, although useful, is not free (implementation cost). Access controls with authentication & authorization for local and remote access. MS Windows has it, otherwise use OpenLDAP, OpenIAM, etc. Application security Everyone tries to reinvent the wheel—use existing static analysis tools. Review high-risk apps and major revisions. Don't run different risk level apps on same system. Assume host/client compromised and use app-level security control. Network security VLAN != segregated because there's too many workarounds. Use explicit firwall rules, active and passive network monitoring (snort is free), disallow end user access to production environment, have a proxy instead of direct Internet access. Also, SSL certificates are not good two-factor auth and SSL does not mean "safe." Operational Controls Have change, patch, asset, & vulnerability management (OSSI is free). For change management, always review code before pushing to production For logging, have centralized security logging for business-critical systems, separate security logging from administrative/IT logging, and lock down log (as it has everything). Monitor with OSSIM (open source). Use intrusion detection, but not just to fulfill a checkbox: build rules from a whitelist perspective (snort). OSSEC has 95% of what you need. Vulnerability management is a QA function when done right: OpenVas and Seccubus are free. Security awareness The reality is users will always click everything. Build real awareness, not compliance driven checkbox, and have it integrated into the culture. Pen test by crowd sourcing—test with logging COSSP http://www.cossp.org/ - Comprehensive Open Source Security Project What Journalists Want: The Investigative Reporters' Perspective on Hacking Dave Maas, San Diego CityBeat Jason Leopold, Truthout.org The difference between hackers and investigative journalists: For hackers, the motivation varies, but method is same, technological specialties. For investigative journalists, it's about one thing—The Story, and they need broad info-gathering skills. J-School in 60 Seconds: Generic formula: Person or issue of pubic interest, new info, or angle. Generic criteria: proximity, prominence, timeliness, human interest, oddity, or consequence. Media awareness of hackers and trends: journalists becoming extremely aware of hackers with congressional debates (privacy, data breaches), demand for data-mining Journalists, use of coding and web development for Journalists, and Journalists busted for hacking (Murdock). Info gathering by investigative journalists include Public records laws. Federal Freedom of Information Act (FOIA) is good, but slow. California Public Records Act is a lot stronger. FOIA takes forever because of foot-dragging—it helps to be specific. Often need to sue (especially FBI). CPRA is faster, and requests can be vague. Dumps and leaks (a la Wikileaks) Journalists want: leads, protecting ourselves, our sources, and adapting tools for news gathering (Google hacking). Anonomity is important to whistleblowers. They want no digital footprint left behind (e.g., email, web log). They don't trust encryption, want to feel safe and secure. Whistleblower laws are very weak—there's no upside for whistleblowers—they have to be very passionate to do it. Accessibility and Security or: How I Learned to Stop Worrying and Love the Halting Problem Anna Shubina, Dartmouth College Anna talked about how accessibility and security are related. Accessibility of digital content (not real world accessibility). mostly refers to blind users and screenreaders, for our purpose. Accessibility is about parsing documents, as are many security issues. "Rich" executable content causes accessibility to fail, and often causes security to fail. For example MS Word has executable format—it's not a document exchange format—more dangerous than PDF or HTML. Accessibility is often the first and maybe only sanity check with parsing. They have no choice because someone may want to read what you write. Google, for example, is very particular about web browser you use and are bad at supporting other browsers. Uses JavaScript instead of links, often requiring mouseover to display content. PDF is a security nightmare. Executible format, embedded flash, JavaScript, etc. 15 million lines of code. Google Chrome doesn't handle PDF correctly, causing several security bugs. PDF has an accessibility checker and PDF tagging, to help with accessibility. But no PDF checker checks for incorrect tags, untagged content, or validates lists or tables. None check executable content at all. The "Halting Problem" is: can one decide whether a program will ever stop? The answer, in general, is no (Rice's theorem). The same holds true for accessibility checkers. Language-theoretic Security says complicated data formats are hard to parse and cannot be solved due to the Halting Problem. W3C Web Accessibility Guidelines: "Perceivable, Operable, Understandable, Robust" Not much help though, except for "Robust", but here's some gems: * all information should be parsable (paraphrasing) * if not parsable, cannot be converted to alternate formats * maximize compatibility in new document formats Executible webpages are bad for security and accessibility. They say it's for a better web experience. But is it necessary to stuff web pages with JavaScript for a better experience? A good example is The Drudge Report—it has hand-written HTML with no JavaScript, yet drives a lot of web traffic due to good content. A bad example is Google News—hidden scrollbars, guessing user input. Solutions: Accessibility and security problems come from same source Expose "better user experience" myth Keep your corner of Internet parsable Remember "Halting Problem"—recognize false solutions (checking and verifying tools) Stop Patching, for Stronger PCI Compliance Adam Brand, protiviti @adamrbrand, http://www.picfun.com/ Adam talked about PCI compliance for retail sales. Take an example: for PCI compliance, 50% of Brian's time (a IT guy), 960 hours/year was spent patching POSs in 850 restaurants. Often applying some patches make no sense (like fixing a browser vulnerability on a server). "Scanner worship" is overuse of vulnerability scanners—it gives a warm and fuzzy and it's simple (red or green results—fix reds). Scanners give a false sense of security. In reality, breeches from missing patches are uncommon—more common problems are: default passwords, cleartext authentication, misconfiguration (firewall ports open). Patching Myths: Myth 1: install within 30 days of patch release (but PCI §6.1 allows a "risk-based approach" instead). Myth 2: vendor decides what's critical (also PCI §6.1). But §6.2 requires user ranking of vulnerabilities instead. Myth 3: scan and rescan until it passes. But PCI §11.2.1b says this applies only to high-risk vulnerabilities. Adam says good recommendations come from NIST 800-40. Instead use sane patching and focus on what's really important. From NIST 800-40: Proactive: Use a proactive vulnerability management process: use change control, configuration management, monitor file integrity. Monitor: start with NVD and other vulnerability alerts, not scanner results. Evaluate: public-facing system? workstation? internal server? (risk rank) Decide:on action and timeline Test: pre-test patches (stability, functionality, rollback) for change control Install: notify, change control, tickets McAfee Secure & Trustmarks — a Hacker's Best Friend Jay James, Shane MacDougall, Tactical Intelligence Inc., Canada "McAfee Secure Trustmark" is a website seal marketed by McAfee. A website gets this badge if they pass their remote scanning. The problem is a removal of trustmarks act as flags that you're vulnerable. Easy to view status change by viewing McAfee list on website or on Google. "Secure TrustGuard" is similar to McAfee. Jay and Shane wrote Perl scripts to gather sites from McAfee and search engines. If their certification image changes to a 1x1 pixel image, then they are longer certified. Their scripts take deltas of scans to see what changed daily. The bottom line is change in TrustGuard status is a flag for hackers to attack your site. Entire idea of seals is silly—you're raising a flag saying if you're vulnerable.

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  • which performance counters mainly matter for windows server performance?

    - by Karl Cassar
    We have a website which is sometimes performing slowly, and / or completely hangs. I have setted up temporarily the default system performance data collector in Performance Monitor, to see if this can shed some light. However, the default Data Collector set collects a huge amount of counters, as well as generates huge logs files. Just 8 hours of data resulted in 4GB of data. Which performance counters matter the most, when judging server load? Also, is it a performance concern if one leaves such data-collectors running indefinitely? Obviously, I will not know when the server will experience slow performance, so I need the logs there so that I can check them out. Any other specific guidelines on monitoring server performance would be greatly appreciated. OS is a Windows Server 2008 R2 (Web Edition).

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  • Toorcon 15 (2013)

    - by danx
    The Toorcon gang (senior staff): h1kari (founder), nfiltr8, and Geo Introduction to Toorcon 15 (2013) A Tale of One Software Bypass of MS Windows 8 Secure Boot Breaching SSL, One Byte at a Time Running at 99%: Surviving an Application DoS Security Response in the Age of Mass Customized Attacks x86 Rewriting: Defeating RoP and other Shinanighans Clowntown Express: interesting bugs and running a bug bounty program Active Fingerprinting of Encrypted VPNs Making Attacks Go Backwards Mask Your Checksums—The Gorry Details Adventures with weird machines thirty years after "Reflections on Trusting Trust" Introduction to Toorcon 15 (2013) Toorcon 15 is the 15th annual security conference held in San Diego. I've attended about a third of them and blogged about previous conferences I attended here starting in 2003. As always, I've only summarized the talks I attended and interested me enough to write about them. Be aware that I may have misrepresented the speaker's remarks and that they are not my remarks or opinion, or those of my employer, so don't quote me or them. Those seeking further details may contact the speakers directly or use The Google. For some talks, I have a URL for further information. A Tale of One Software Bypass of MS Windows 8 Secure Boot Andrew Furtak and Oleksandr Bazhaniuk Yuri Bulygin, Oleksandr ("Alex") Bazhaniuk, and (not present) Andrew Furtak Yuri and Alex talked about UEFI and Bootkits and bypassing MS Windows 8 Secure Boot, with vendor recommendations. They previously gave this talk at the BlackHat 2013 conference. MS Windows 8 Secure Boot Overview UEFI (Unified Extensible Firmware Interface) is interface between hardware and OS. UEFI is processor and architecture independent. Malware can replace bootloader (bootx64.efi, bootmgfw.efi). Once replaced can modify kernel. Trivial to replace bootloader. Today many legacy bootkits—UEFI replaces them most of them. MS Windows 8 Secure Boot verifies everything you load, either through signatures or hashes. UEFI firmware relies on secure update (with signed update). You would think Secure Boot would rely on ROM (such as used for phones0, but you can't do that for PCs—PCs use writable memory with signatures DXE core verifies the UEFI boat loader(s) OS Loader (winload.efi, winresume.efi) verifies the OS kernel A chain of trust is established with a root key (Platform Key, PK), which is a cert belonging to the platform vendor. Key Exchange Keys (KEKs) verify an "authorized" database (db), and "forbidden" database (dbx). X.509 certs with SHA-1/SHA-256 hashes. Keys are stored in non-volatile (NV) flash-based NVRAM. Boot Services (BS) allow adding/deleting keys (can't be accessed once OS starts—which uses Run-Time (RT)). Root cert uses RSA-2048 public keys and PKCS#7 format signatures. SecureBoot — enable disable image signature checks SetupMode — update keys, self-signed keys, and secure boot variables CustomMode — allows updating keys Secure Boot policy settings are: always execute, never execute, allow execute on security violation, defer execute on security violation, deny execute on security violation, query user on security violation Attacking MS Windows 8 Secure Boot Secure Boot does NOT protect from physical access. Can disable from console. Each BIOS vendor implements Secure Boot differently. There are several platform and BIOS vendors. It becomes a "zoo" of implementations—which can be taken advantage of. Secure Boot is secure only when all vendors implement it correctly. Allow only UEFI firmware signed updates protect UEFI firmware from direct modification in flash memory protect FW update components program SPI controller securely protect secure boot policy settings in nvram protect runtime api disable compatibility support module which allows unsigned legacy Can corrupt the Platform Key (PK) EFI root certificate variable in SPI flash. If PK is not found, FW enters setup mode wich secure boot turned off. Can also exploit TPM in a similar manner. One is not supposed to be able to directly modify the PK in SPI flash from the OS though. But they found a bug that they can exploit from User Mode (undisclosed) and demoed the exploit. It loaded and ran their own bootkit. The exploit requires a reboot. Multiple vendors are vulnerable. They will disclose this exploit to vendors in the future. Recommendations: allow only signed updates protect UEFI fw in ROM protect EFI variable store in ROM Breaching SSL, One Byte at a Time Yoel Gluck and Angelo Prado Angelo Prado and Yoel Gluck, Salesforce.com CRIME is software that performs a "compression oracle attack." This is possible because the SSL protocol doesn't hide length, and because SSL compresses the header. CRIME requests with every possible character and measures the ciphertext length. Look for the plaintext which compresses the most and looks for the cookie one byte-at-a-time. SSL Compression uses LZ77 to reduce redundancy. Huffman coding replaces common byte sequences with shorter codes. US CERT thinks the SSL compression problem is fixed, but it isn't. They convinced CERT that it wasn't fixed and they issued a CVE. BREACH, breachattrack.com BREACH exploits the SSL response body (Accept-Encoding response, Content-Encoding). It takes advantage of the fact that the response is not compressed. BREACH uses gzip and needs fairly "stable" pages that are static for ~30 seconds. It needs attacker-supplied content (say from a web form or added to a URL parameter). BREACH listens to a session's requests and responses, then inserts extra requests and responses. Eventually, BREACH guesses a session's secret key. Can use compression to guess contents one byte at-a-time. For example, "Supersecret SupersecreX" (a wrong guess) compresses 10 bytes, and "Supersecret Supersecret" (a correct guess) compresses 11 bytes, so it can find each character by guessing every character. To start the guess, BREACH needs at least three known initial characters in the response sequence. Compression length then "leaks" information. Some roadblocks include no winners (all guesses wrong) or too many winners (multiple possibilities that compress the same). The solutions include: lookahead (guess 2 or 3 characters at-a-time instead of 1 character). Expensive rollback to last known conflict check compression ratio can brute-force first 3 "bootstrap" characters, if needed (expensive) block ciphers hide exact plain text length. Solution is to align response in advance to block size Mitigations length: use variable padding secrets: dynamic CSRF tokens per request secret: change over time separate secret to input-less servlets Future work eiter understand DEFLATE/GZIP HTTPS extensions Running at 99%: Surviving an Application DoS Ryan Huber Ryan Huber, Risk I/O Ryan first discussed various ways to do a denial of service (DoS) attack against web services. One usual method is to find a slow web page and do several wgets. Or download large files. Apache is not well suited at handling a large number of connections, but one can put something in front of it Can use Apache alternatives, such as nginx How to identify malicious hosts short, sudden web requests user-agent is obvious (curl, python) same url requested repeatedly no web page referer (not normal) hidden links. hide a link and see if a bot gets it restricted access if not your geo IP (unless the website is global) missing common headers in request regular timing first seen IP at beginning of attack count requests per hosts (usually a very large number) Use of captcha can mitigate attacks, but you'll lose a lot of genuine users. Bouncer, goo.gl/c2vyEc and www.github.com/rawdigits/Bouncer Bouncer is software written by Ryan in netflow. Bouncer has a small, unobtrusive footprint and detects DoS attempts. It closes blacklisted sockets immediately (not nice about it, no proper close connection). Aggregator collects requests and controls your web proxies. Need NTP on the front end web servers for clean data for use by bouncer. Bouncer is also useful for a popularity storm ("Slashdotting") and scraper storms. Future features: gzip collection data, documentation, consumer library, multitask, logging destroyed connections. Takeaways: DoS mitigation is easier with a complete picture Bouncer designed to make it easier to detect and defend DoS—not a complete cure Security Response in the Age of Mass Customized Attacks Peleus Uhley and Karthik Raman Peleus Uhley and Karthik Raman, Adobe ASSET, blogs.adobe.com/asset/ Peleus and Karthik talked about response to mass-customized exploits. Attackers behave much like a business. "Mass customization" refers to concept discussed in the book Future Perfect by Stan Davis of Harvard Business School. Mass customization is differentiating a product for an individual customer, but at a mass production price. For example, the same individual with a debit card receives basically the same customized ATM experience around the world. Or designing your own PC from commodity parts. Exploit kits are another example of mass customization. The kits support multiple browsers and plugins, allows new modules. Exploit kits are cheap and customizable. Organized gangs use exploit kits. A group at Berkeley looked at 77,000 malicious websites (Grier et al., "Manufacturing Compromise: The Emergence of Exploit-as-a-Service", 2012). They found 10,000 distinct binaries among them, but derived from only a dozen or so exploit kits. Characteristics of Mass Malware: potent, resilient, relatively low cost Technical characteristics: multiple OS, multipe payloads, multiple scenarios, multiple languages, obfuscation Response time for 0-day exploits has gone down from ~40 days 5 years ago to about ~10 days now. So the drive with malware is towards mass customized exploits, to avoid detection There's plenty of evicence that exploit development has Project Manager bureaucracy. They infer from the malware edicts to: support all versions of reader support all versions of windows support all versions of flash support all browsers write large complex, difficult to main code (8750 lines of JavaScript for example Exploits have "loose coupling" of multipe versions of software (adobe), OS, and browser. This allows specific attacks against specific versions of multiple pieces of software. Also allows exploits of more obscure software/OS/browsers and obscure versions. Gave examples of exploits that exploited 2, 3, 6, or 14 separate bugs. However, these complete exploits are more likely to be buggy or fragile in themselves and easier to defeat. Future research includes normalizing malware and Javascript. Conclusion: The coming trend is that mass-malware with mass zero-day attacks will result in mass customization of attacks. x86 Rewriting: Defeating RoP and other Shinanighans Richard Wartell Richard Wartell The attack vector we are addressing here is: First some malware causes a buffer overflow. The malware has no program access, but input access and buffer overflow code onto stack Later the stack became non-executable. The workaround malware used was to write a bogus return address to the stack jumping to malware Later came ASLR (Address Space Layout Randomization) to randomize memory layout and make addresses non-deterministic. The workaround malware used was to jump t existing code segments in the program that can be used in bad ways "RoP" is Return-oriented Programming attacks. RoP attacks use your own code and write return address on stack to (existing) expoitable code found in program ("gadgets"). Pinkie Pie was paid $60K last year for a RoP attack. One solution is using anti-RoP compilers that compile source code with NO return instructions. ASLR does not randomize address space, just "gadgets". IPR/ILR ("Instruction Location Randomization") randomizes each instruction with a virtual machine. Richard's goal was to randomize a binary with no source code access. He created "STIR" (Self-Transofrming Instruction Relocation). STIR disassembles binary and operates on "basic blocks" of code. The STIR disassembler is conservative in what to disassemble. Each basic block is moved to a random location in memory. Next, STIR writes new code sections with copies of "basic blocks" of code in randomized locations. The old code is copied and rewritten with jumps to new code. the original code sections in the file is marked non-executible. STIR has better entropy than ASLR in location of code. Makes brute force attacks much harder. STIR runs on MS Windows (PEM) and Linux (ELF). It eliminated 99.96% or more "gadgets" (i.e., moved the address). Overhead usually 5-10% on MS Windows, about 1.5-4% on Linux (but some code actually runs faster!). The unique thing about STIR is it requires no source access and the modified binary fully works! Current work is to rewrite code to enforce security policies. For example, don't create a *.{exe,msi,bat} file. Or don't connect to the network after reading from the disk. Clowntown Express: interesting bugs and running a bug bounty program Collin Greene Collin Greene, Facebook Collin talked about Facebook's bug bounty program. Background at FB: FB has good security frameworks, such as security teams, external audits, and cc'ing on diffs. But there's lots of "deep, dark, forgotten" parts of legacy FB code. Collin gave several examples of bountied bugs. Some bounty submissions were on software purchased from a third-party (but bounty claimers don't know and don't care). We use security questions, as does everyone else, but they are basically insecure (often easily discoverable). Collin didn't expect many bugs from the bounty program, but they ended getting 20+ good bugs in first 24 hours and good submissions continue to come in. Bug bounties bring people in with different perspectives, and are paid only for success. Bug bounty is a better use of a fixed amount of time and money versus just code review or static code analysis. The Bounty program started July 2011 and paid out $1.5 million to date. 14% of the submissions have been high priority problems that needed to be fixed immediately. The best bugs come from a small % of submitters (as with everything else)—the top paid submitters are paid 6 figures a year. Spammers like to backstab competitors. The youngest sumitter was 13. Some submitters have been hired. Bug bounties also allows to see bugs that were missed by tools or reviews, allowing improvement in the process. Bug bounties might not work for traditional software companies where the product has release cycle or is not on Internet. Active Fingerprinting of Encrypted VPNs Anna Shubina Anna Shubina, Dartmouth Institute for Security, Technology, and Society (I missed the start of her talk because another track went overtime. But I have the DVD of the talk, so I'll expand later) IPsec leaves fingerprints. Using netcat, one can easily visually distinguish various crypto chaining modes just from packet timing on a chart (example, DES-CBC versus AES-CBC) One can tell a lot about VPNs just from ping roundtrips (such as what router is used) Delayed packets are not informative about a network, especially if far away from the network More needed to explore about how TCP works in real life with respect to timing Making Attacks Go Backwards Fuzzynop FuzzyNop, Mandiant This talk is not about threat attribution (finding who), product solutions, politics, or sales pitches. But who are making these malware threats? It's not a single person or group—they have diverse skill levels. There's a lot of fat-fingered fumblers out there. Always look for low-hanging fruit first: "hiding" malware in the temp, recycle, or root directories creation of unnamed scheduled tasks obvious names of files and syscalls ("ClearEventLog") uncleared event logs. Clearing event log in itself, and time of clearing, is a red flag and good first clue to look for on a suspect system Reverse engineering is hard. Disassembler use takes practice and skill. A popular tool is IDA Pro, but it takes multiple interactive iterations to get a clean disassembly. Key loggers are used a lot in targeted attacks. They are typically custom code or built in a backdoor. A big tip-off is that non-printable characters need to be printed out (such as "[Ctrl]" "[RightShift]") or time stamp printf strings. Look for these in files. Presence is not proof they are used. Absence is not proof they are not used. Java exploits. Can parse jar file with idxparser.py and decomile Java file. Java typially used to target tech companies. Backdoors are the main persistence mechanism (provided externally) for malware. Also malware typically needs command and control. Application of Artificial Intelligence in Ad-Hoc Static Code Analysis John Ashaman John Ashaman, Security Innovation Initially John tried to analyze open source files with open source static analysis tools, but these showed thousands of false positives. Also tried using grep, but tis fails to find anything even mildly complex. So next John decided to write his own tool. His approach was to first generate a call graph then analyze the graph. However, the problem is that making a call graph is really hard. For example, one problem is "evil" coding techniques, such as passing function pointer. First the tool generated an Abstract Syntax Tree (AST) with the nodes created from method declarations and edges created from method use. Then the tool generated a control flow graph with the goal to find a path through the AST (a maze) from source to sink. The algorithm is to look at adjacent nodes to see if any are "scary" (a vulnerability), using heuristics for search order. The tool, called "Scat" (Static Code Analysis Tool), currently looks for C# vulnerabilities and some simple PHP. Later, he plans to add more PHP, then JSP and Java. For more information see his posts in Security Innovation blog and NRefactory on GitHub. Mask Your Checksums—The Gorry Details Eric (XlogicX) Davisson Eric (XlogicX) Davisson Sometimes in emailing or posting TCP/IP packets to analyze problems, you may want to mask the IP address. But to do this correctly, you need to mask the checksum too, or you'll leak information about the IP. Problem reports found in stackoverflow.com, sans.org, and pastebin.org are usually not masked, but a few companies do care. If only the IP is masked, the IP may be guessed from checksum (that is, it leaks data). Other parts of packet may leak more data about the IP. TCP and IP checksums both refer to the same data, so can get more bits of information out of using both checksums than just using one checksum. Also, one can usually determine the OS from the TTL field and ports in a packet header. If we get hundreds of possible results (16x each masked nibble that is unknown), one can do other things to narrow the results, such as look at packet contents for domain or geo information. With hundreds of results, can import as CSV format into a spreadsheet. Can corelate with geo data and see where each possibility is located. Eric then demoed a real email report with a masked IP packet attached. Was able to find the exact IP address, given the geo and university of the sender. Point is if you're going to mask a packet, do it right. Eric wouldn't usually bother, but do it correctly if at all, to not create a false impression of security. Adventures with weird machines thirty years after "Reflections on Trusting Trust" Sergey Bratus Sergey Bratus, Dartmouth College (and Julian Bangert and Rebecca Shapiro, not present) "Reflections on Trusting Trust" refers to Ken Thompson's classic 1984 paper. "You can't trust code that you did not totally create yourself." There's invisible links in the chain-of-trust, such as "well-installed microcode bugs" or in the compiler, and other planted bugs. Thompson showed how a compiler can introduce and propagate bugs in unmodified source. But suppose if there's no bugs and you trust the author, can you trust the code? Hell No! There's too many factors—it's Babylonian in nature. Why not? Well, Input is not well-defined/recognized (code's assumptions about "checked" input will be violated (bug/vunerabiliy). For example, HTML is recursive, but Regex checking is not recursive. Input well-formed but so complex there's no telling what it does For example, ELF file parsing is complex and has multiple ways of parsing. Input is seen differently by different pieces of program or toolchain Any Input is a program input executes on input handlers (drives state changes & transitions) only a well-defined execution model can be trusted (regex/DFA, PDA, CFG) Input handler either is a "recognizer" for the inputs as a well-defined language (see langsec.org) or it's a "virtual machine" for inputs to drive into pwn-age ELF ABI (UNIX/Linux executible file format) case study. Problems can arise from these steps (without planting bugs): compiler linker loader ld.so/rtld relocator DWARF (debugger info) exceptions The problem is you can't really automatically analyze code (it's the "halting problem" and undecidable). Only solution is to freeze code and sign it. But you can't freeze everything! Can't freeze ASLR or loading—must have tables and metadata. Any sufficiently complex input data is the same as VM byte code Example, ELF relocation entries + dynamic symbols == a Turing Complete Machine (TM). @bxsays created a Turing machine in Linux from relocation data (not code) in an ELF file. For more information, see Rebecca "bx" Shapiro's presentation from last year's Toorcon, "Programming Weird Machines with ELF Metadata" @bxsays did same thing with Mach-O bytecode Or a DWARF exception handling data .eh_frame + glibc == Turning Machine X86 MMU (IDT, GDT, TSS): used address translation to create a Turning Machine. Page handler reads and writes (on page fault) memory. Uses a page table, which can be used as Turning Machine byte code. Example on Github using this TM that will fly a glider across the screen Next Sergey talked about "Parser Differentials". That having one input format, but two parsers, will create confusion and opportunity for exploitation. For example, CSRs are parsed during creation by cert requestor and again by another parser at the CA. Another example is ELF—several parsers in OS tool chain, which are all different. Can have two different Program Headers (PHDRs) because ld.so parses multiple PHDRs. The second PHDR can completely transform the executable. This is described in paper in the first issue of International Journal of PoC. Conclusions trusting computers not only about bugs! Bugs are part of a problem, but no by far all of it complex data formats means bugs no "chain of trust" in Babylon! (that is, with parser differentials) we need to squeeze complexity out of data until data stops being "code equivalent" Further information See and langsec.org. USENIX WOOT 2013 (Workshop on Offensive Technologies) for "weird machines" papers and videos.

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  • TDE Tablespace Encryption 11.2.0.1 Certified with EBS 12

    - by Steven Chan
    Oracle Advanced Security is an optional licenced Oracle 11g Database add-on.  Oracle Advanced Security Transparent Data Encryption (TDE) offers two different features:  column encryption and tablespace encryption.  11.2.0.1 TDE Column encryption was certified with E-Business Suite 12 as part of our overall 11.2.0.1 database certification.  As of today, 11.2.0.1 TDE Tablespace encryption is now certified with Oracle E-Business Suite Release 12. What is Transparent Data Encryption (TDE) ? Oracle Advanced Security Transparent Data Encryption (TDE) allows you to protect data at rest. TDE helps address privacy and PCI requirements by encrypting personally identifiable information (PII) such as Social Security numbers and credit card numbers. TDE is completely transparent to existing applications with no triggers, views or other application changes required. Data is transparently encrypted when written to disk and transparently decrypted after an application user has successfully authenticated and passed all authorization checks. Authorization checks include verifying the user has the necessary select and update privileges on the application table and checking Database Vault, Label Security and Virtual Private Database enforcement policies.

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  • How to: Check which table is the biggest, in SQL Server

    - by AngelEyes
    The company I work with had it's DB double its size lately, so I needed to find out which tables were the biggest. I found this on the web, and decided it's worth remembering! Taken from http://www.sqlteam.com/article/finding-the-biggest-tables-in-a-database, the code is from http://www.sqlteam.com/downloads/BigTables.sql   /************************************************************************************** * *  BigTables.sql *  Bill Graziano (SQLTeam.com) *  [email protected] *  v1.1 * **************************************************************************************/ DECLARE @id INT DECLARE @type CHARACTER(2) DECLARE @pages INT DECLARE @dbname SYSNAME DECLARE @dbsize DEC(15, 0) DECLARE @bytesperpage DEC(15, 0) DECLARE @pagesperMB DEC(15, 0) CREATE TABLE #spt_space   (      objid    INT NULL,      ROWS     INT NULL,      reserved DEC(15) NULL,      data     DEC(15) NULL,      indexp   DEC(15) NULL,      unused   DEC(15) NULL   ) SET nocount ON -- Create a cursor to loop through the user tables DECLARE c_tables CURSOR FOR   SELECT id   FROM   sysobjects   WHERE  xtype = 'U' OPEN c_tables FETCH NEXT FROM c_tables INTO @id WHILE @@FETCH_STATUS = 0   BEGIN       /* Code from sp_spaceused */       INSERT INTO #spt_space                   (objid,                    reserved)       SELECT objid = @id,              SUM(reserved)       FROM   sysindexes       WHERE  indid IN ( 0, 1, 255 )              AND id = @id       SELECT @pages = SUM(dpages)       FROM   sysindexes       WHERE  indid < 2              AND id = @id       SELECT @pages = @pages + Isnull(SUM(used), 0)       FROM   sysindexes       WHERE  indid = 255              AND id = @id       UPDATE #spt_space       SET    data = @pages       WHERE  objid = @id       /* index: sum(used) where indid in (0, 1, 255) - data */       UPDATE #spt_space       SET    indexp = (SELECT SUM(used)                        FROM   sysindexes                        WHERE  indid IN ( 0, 1, 255 )                               AND id = @id) - data       WHERE  objid = @id       /* unused: sum(reserved) - sum(used) where indid in (0, 1, 255) */       UPDATE #spt_space       SET    unused = reserved - (SELECT SUM(used)                                   FROM   sysindexes                                   WHERE  indid IN ( 0, 1, 255 )                                          AND id = @id)       WHERE  objid = @id       UPDATE #spt_space       SET    ROWS = i.ROWS       FROM   sysindexes i       WHERE  i.indid < 2              AND i.id = @id              AND objid = @id       FETCH NEXT FROM c_tables INTO @id   END SELECT TOP 25 table_name = (SELECT LEFT(name, 25)                             FROM   sysobjects                             WHERE  id = objid),               ROWS = CONVERT(CHAR(11), ROWS),               reserved_kb = Ltrim(Str(reserved * d.low / 1024., 15, 0) + ' ' + 'KB'),               data_kb = Ltrim(Str(data * d.low / 1024., 15, 0) + ' ' + 'KB'),               index_size_kb = Ltrim(Str(indexp * d.low / 1024., 15, 0) + ' ' + 'KB'),               unused_kb = Ltrim(Str(unused * d.low / 1024., 15, 0) + ' ' + 'KB') FROM   #spt_space,        MASTER.dbo.spt_values d WHERE  d.NUMBER = 1        AND d.TYPE = 'E' ORDER  BY reserved DESC DROP TABLE #spt_space CLOSE c_tables DEALLOCATE c_tables

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  • SQL Server 2012 - AlwaysOn

    - by Claus Jandausch
    Ich war nicht nur irritiert, ich war sogar regelrecht schockiert - und für einen kurzen Moment sprachlos (was nur selten der Fall ist). Gerade eben hatte mich jemand gefragt "Wann Oracle denn etwas Vergleichbares wie AlwaysOn bieten würde - und ob überhaupt?" War ich hier im falschen Film gelandet? Ich konnte nicht anders, als meinen Unmut kundzutun und zu erklären, dass die Fragestellung normalerweise anders herum läuft. Zugegeben - es mag vielleicht strittige Punkte geben im Vergleich zwischen Oracle und SQL Server - bei denen nicht unbedingt immer Oracle die Nase vorn haben muss - aber das Thema Clustering für Hochverfügbarkeit (HA), Disaster Recovery (DR) und Skalierbarkeit gehört mit Sicherheit nicht dazu. Dieses Erlebnis hakte ich am Nachgang als Einzelfall ab, der so nie wieder vorkommen würde. Bis ich kurz darauf eines Besseren belehrt wurde und genau die selbe Frage erneut zu hören bekam. Diesmal sogar im Exadata-Umfeld und einem Oracle Stretch Cluster. Einmal ist keinmal, doch zweimal ist einmal zu viel... Getreu diesem alten Motto war mir klar, dass man das so nicht länger stehen lassen konnte. Ich habe keine Ahnung, wie die Microsoft Marketing Abteilung es geschafft hat, unter dem AlwaysOn Brading eine innovative Technologie vermuten zu lassen - aber sie hat ihren Job scheinbar gut gemacht. Doch abgesehen von einem guten Marketing, stellt sich natürlich die Frage, was wirklich dahinter steckt und wie sich das Ganze mit Oracle vergleichen lässt - und ob überhaupt? Damit wären wir wieder bei der ursprünglichen Frage angelangt.  So viel zum Hintergrund dieses Blogbeitrags - von meiner Antwort handelt der restliche Blog. "Windows was the God ..." Um den wahren Unterschied zwischen Oracle und Microsoft verstehen zu können, muss man zunächst das bedeutendste Microsoft Dogma kennen. Es lässt sich schlicht und einfach auf den Punkt bringen: "Alles muss auf Windows basieren." Die Überschrift dieses Absatzes ist kein von mir erfundener Ausspruch, sondern ein Zitat. Konkret stammt es aus einem längeren Artikel von Kurt Eichenwald in der Vanity Fair aus dem August 2012. Er lautet Microsoft's Lost Decade und sei jedem ans Herz gelegt, der die "Microsoft-Maschinerie" unter Steve Ballmer und einige ihrer Kuriositäten besser verstehen möchte. "YOU TALKING TO ME?" Microsoft C.E.O. Steve Ballmer bei seiner Keynote auf der 2012 International Consumer Electronics Show in Las Vegas am 9. Januar   Manche Dinge in diesem Artikel mögen überspitzt dargestellt erscheinen - sind sie aber nicht. Vieles davon kannte ich bereits aus eigener Erfahrung und kann es nur bestätigen. Anderes hat sich mir erst so richtig erschlossen. Insbesondere die folgenden Passagen führten zum Aha-Erlebnis: “Windows was the god—everything had to work with Windows,” said Stone... “Every little thing you want to write has to build off of Windows (or other existing roducts),” one software engineer said. “It can be very confusing, …” Ich habe immer schon darauf hingewiesen, dass in einem SQL Server Failover Cluster die Microsoft Datenbank eigentlich nichts Nenneswertes zum Geschehen beiträgt, sondern sich voll und ganz auf das Windows Betriebssystem verlässt. Deshalb muss man auch die Windows Server Enterprise Edition installieren, soll ein Failover Cluster für den SQL Server eingerichtet werden. Denn hier werden die Cluster Services geliefert - nicht mit dem SQL Server. Er ist nur lediglich ein weiteres Server Produkt, für das Windows in Ausfallszenarien genutzt werden kann - so wie Microsoft Exchange beispielsweise, oder Microsoft SharePoint, oder irgendein anderes Server Produkt das auf Windows gehostet wird. Auch Oracle kann damit genutzt werden. Das Stichwort lautet hier: Oracle Failsafe. Nur - warum sollte man das tun, wenn gleichzeitig eine überlegene Technologie wie die Oracle Real Application Clusters (RAC) zur Verfügung steht, die dann auch keine Windows Enterprise Edition voraussetzen, da Oracle die eigene Clusterware liefert. Welche darüber hinaus für kürzere Failover-Zeiten sorgt, da diese Cluster-Technologie Datenbank-integriert ist und sich nicht auf "Dritte" verlässt. Wenn man sich also schon keine technischen Vorteile mit einem SQL Server Failover Cluster erkauft, sondern zusätzlich noch versteckte Lizenzkosten durch die Lizenzierung der Windows Server Enterprise Edition einhandelt, warum hat Microsoft dann in den vergangenen Jahren seit SQL Server 2000 nicht ebenfalls an einer neuen und innovativen Lösung gearbeitet, die mit Oracle RAC mithalten kann? Entwickler hat Microsoft genügend? Am Geld kann es auch nicht liegen? Lesen Sie einfach noch einmal die beiden obenstehenden Zitate und sie werden den Grund verstehen. Anders lässt es sich ja auch gar nicht mehr erklären, dass AlwaysOn aus zwei unterschiedlichen Technologien besteht, die beide jedoch wiederum auf dem Windows Server Failover Clustering (WSFC) basieren. Denn daraus ergeben sich klare Nachteile - aber dazu später mehr. Um AlwaysOn zu verstehen, sollte man sich zunächst kurz in Erinnerung rufen, was Microsoft bisher an HA/DR (High Availability/Desaster Recovery) Lösungen für SQL Server zur Verfügung gestellt hat. Replikation Basiert auf logischer Replikation und Pubisher/Subscriber Architektur Transactional Replication Merge Replication Snapshot Replication Microsoft's Replikation ist vergleichbar mit Oracle GoldenGate. Oracle GoldenGate stellt jedoch die umfassendere Technologie dar und bietet High Performance. Log Shipping Microsoft's Log Shipping stellt eine einfache Technologie dar, die vergleichbar ist mit Oracle Managed Recovery in Oracle Version 7. Das Log Shipping besitzt folgende Merkmale: Transaction Log Backups werden von Primary nach Secondary/ies geschickt Einarbeitung (z.B. Restore) auf jedem Secondary individuell Optionale dritte Server Instanz (Monitor Server) für Überwachung und Alarm Log Restore Unterbrechung möglich für Read-Only Modus (Secondary) Keine Unterstützung von Automatic Failover Database Mirroring Microsoft's Database Mirroring wurde verfügbar mit SQL Server 2005, sah aus wie Oracle Data Guard in Oracle 9i, war funktional jedoch nicht so umfassend. Für ein HA/DR Paar besteht eine 1:1 Beziehung, um die produktive Datenbank (Principle DB) abzusichern. Auf der Standby Datenbank (Mirrored DB) werden alle Insert-, Update- und Delete-Operationen nachgezogen. Modi Synchron (High-Safety Modus) Asynchron (High-Performance Modus) Automatic Failover Unterstützt im High-Safety Modus (synchron) Witness Server vorausgesetzt     Zur Frage der Kontinuität Es stellt sich die Frage, wie es um diesen Technologien nun im Zusammenhang mit SQL Server 2012 bestellt ist. Unter Fanfaren seinerzeit eingeführt, war Database Mirroring das erklärte Mittel der Wahl. Ich bin kein Produkt Manager bei Microsoft und kann hierzu nur meine Meinung äußern, aber zieht man den SQL AlwaysOn Team Blog heran, so sieht es nicht gut aus für das Database Mirroring - zumindest nicht langfristig. "Does AlwaysOn Availability Group replace Database Mirroring going forward?” “The short answer is we recommend that you migrate from the mirroring configuration or even mirroring and log shipping configuration to using Availability Group. Database Mirroring will still be available in the Denali release but will be phased out over subsequent releases. Log Shipping will continue to be available in future releases.” Damit wären wir endlich beim eigentlichen Thema angelangt. Was ist eine sogenannte Availability Group und was genau hat es mit der vielversprechend klingenden Bezeichnung AlwaysOn auf sich?   SQL Server 2012 - AlwaysOn Zwei HA-Features verstekcne sich hinter dem “AlwaysOn”-Branding. Einmal das AlwaysOn Failover Clustering aka SQL Server Failover Cluster Instances (FCI) - zum Anderen die AlwaysOn Availability Groups. Failover Cluster Instances (FCI) Entspricht ungefähr dem Stretch Cluster Konzept von Oracle Setzt auf Windows Server Failover Clustering (WSFC) auf Bietet HA auf Instanz-Ebene AlwaysOn Availability Groups (Verfügbarkeitsgruppen) Ähnlich der Idee von Consistency Groups, wie in Storage-Level Replikations-Software von z.B. EMC SRDF Abhängigkeiten zu Windows Server Failover Clustering (WSFC) Bietet HA auf Datenbank-Ebene   Hinweis: Verwechseln Sie nicht eine SQL Server Datenbank mit einer Oracle Datenbank. Und auch nicht eine Oracle Instanz mit einer SQL Server Instanz. Die gleichen Begriffe haben hier eine andere Bedeutung - nicht selten ein Grund, weshalb Oracle- und Microsoft DBAs schnell aneinander vorbei reden. Denken Sie bei einer SQL Server Datenbank eher an ein Oracle Schema, das kommt der Sache näher. So etwas wie die SQL Server Northwind Datenbank ist vergleichbar mit dem Oracle Scott Schema. Wenn Sie die genauen Unterschiede kennen möchten, finden Sie eine detaillierte Beschreibung in meinem Buch "Oracle10g Release 2 für Windows und .NET", erhältich bei Lehmanns, Amazon, etc.   Windows Server Failover Clustering (WSFC) Wie man sieht, basieren beide AlwaysOn Technologien wiederum auf dem Windows Server Failover Clustering (WSFC), um einerseits Hochverfügbarkeit auf Ebene der Instanz zu gewährleisten und andererseits auf der Datenbank-Ebene. Deshalb nun eine kurze Beschreibung der WSFC. Die WSFC sind ein mit dem Windows Betriebssystem geliefertes Infrastruktur-Feature, um HA für Server Anwendungen, wie Microsoft Exchange, SharePoint, SQL Server, etc. zu bieten. So wie jeder andere Cluster, besteht ein WSFC Cluster aus einer Gruppe unabhängiger Server, die zusammenarbeiten, um die Verfügbarkeit einer Applikation oder eines Service zu erhöhen. Falls ein Cluster-Knoten oder -Service ausfällt, kann der auf diesem Knoten bisher gehostete Service automatisch oder manuell auf einen anderen im Cluster verfügbaren Knoten transferriert werden - was allgemein als Failover bekannt ist. Unter SQL Server 2012 verwenden sowohl die AlwaysOn Avalability Groups, als auch die AlwaysOn Failover Cluster Instances die WSFC als Plattformtechnologie, um Komponenten als WSFC Cluster-Ressourcen zu registrieren. Verwandte Ressourcen werden in eine Ressource Group zusammengefasst, die in Abhängigkeit zu anderen WSFC Cluster-Ressourcen gebracht werden kann. Der WSFC Cluster Service kann jetzt die Notwendigkeit zum Neustart der SQL Server Instanz erfassen oder einen automatischen Failover zu einem anderen Server-Knoten im WSFC Cluster auslösen.   Failover Cluster Instances (FCI) Eine SQL Server Failover Cluster Instanz (FCI) ist eine einzelne SQL Server Instanz, die in einem Failover Cluster betrieben wird, der aus mehreren Windows Server Failover Clustering (WSFC) Knoten besteht und so HA (High Availability) auf Ebene der Instanz bietet. Unter Verwendung von Multi-Subnet FCI kann auch Remote DR (Disaster Recovery) unterstützt werden. Eine weitere Option für Remote DR besteht darin, eine unter FCI gehostete Datenbank in einer Availability Group zu betreiben. Hierzu später mehr. FCI und WSFC Basis FCI, das für lokale Hochverfügbarkeit der Instanzen genutzt wird, ähnelt der veralteten Architektur eines kalten Cluster (Aktiv-Passiv). Unter SQL Server 2008 wurde diese Technologie SQL Server 2008 Failover Clustering genannt. Sie nutzte den Windows Server Failover Cluster. In SQL Server 2012 hat Microsoft diese Basistechnologie unter der Bezeichnung AlwaysOn zusammengefasst. Es handelt sich aber nach wie vor um die klassische Aktiv-Passiv-Konfiguration. Der Ablauf im Failover-Fall ist wie folgt: Solange kein Hardware-oder System-Fehler auftritt, werden alle Dirty Pages im Buffer Cache auf Platte geschrieben Alle entsprechenden SQL Server Services (Dienste) in der Ressource Gruppe werden auf dem aktiven Knoten gestoppt Die Ownership der Ressource Gruppe wird auf einen anderen Knoten der FCI transferriert Der neue Owner (Besitzer) der Ressource Gruppe startet seine SQL Server Services (Dienste) Die Connection-Anforderungen einer Client-Applikation werden automatisch auf den neuen aktiven Knoten mit dem selben Virtuellen Network Namen (VNN) umgeleitet Abhängig vom Zeitpunkt des letzten Checkpoints, kann die Anzahl der Dirty Pages im Buffer Cache, die noch auf Platte geschrieben werden müssen, zu unvorhersehbar langen Failover-Zeiten führen. Um diese Anzahl zu drosseln, besitzt der SQL Server 2012 eine neue Fähigkeit, die Indirect Checkpoints genannt wird. Indirect Checkpoints ähnelt dem Fast-Start MTTR Target Feature der Oracle Datenbank, das bereits mit Oracle9i verfügbar war.   SQL Server Multi-Subnet Clustering Ein SQL Server Multi-Subnet Failover Cluster entspricht vom Konzept her einem Oracle RAC Stretch Cluster. Doch dies ist nur auf den ersten Blick der Fall. Im Gegensatz zu RAC ist in einem lokalen SQL Server Failover Cluster jeweils nur ein Knoten aktiv für eine Datenbank. Für die Datenreplikation zwischen geografisch entfernten Sites verlässt sich Microsoft auf 3rd Party Lösungen für das Storage Mirroring.     Die Verbesserung dieses Szenario mit einer SQL Server 2012 Implementierung besteht schlicht darin, dass eine VLAN-Konfiguration (Virtual Local Area Network) nun nicht mehr benötigt wird, so wie dies bisher der Fall war. Das folgende Diagramm stellt dar, wie der Ablauf mit SQL Server 2012 gehandhabt wird. In Site A und Site B wird HA jeweils durch einen lokalen Aktiv-Passiv-Cluster sichergestellt.     Besondere Aufmerksamkeit muss hier der Konfiguration und dem Tuning geschenkt werden, da ansonsten völlig inakzeptable Failover-Zeiten resultieren. Dies liegt darin begründet, weil die Downtime auf Client-Seite nun nicht mehr nur von der reinen Failover-Zeit abhängt, sondern zusätzlich von der Dauer der DNS Replikation zwischen den DNS Servern. (Rufen Sie sich in Erinnerung, dass wir gerade von Multi-Subnet Clustering sprechen). Außerdem ist zu berücksichtigen, wie schnell die Clients die aktualisierten DNS Informationen abfragen. Spezielle Konfigurationen für Node Heartbeat, HostRecordTTL (Host Record Time-to-Live) und Intersite Replication Frequeny für Active Directory Sites und Services werden notwendig. Default TTL für Windows Server 2008 R2: 20 Minuten Empfohlene Einstellung: 1 Minute DNS Update Replication Frequency in Windows Umgebung: 180 Minuten Empfohlene Einstellung: 15 Minuten (minimaler Wert)   Betrachtet man diese Werte, muss man feststellen, dass selbst eine optimale Konfiguration die rigiden SLAs (Service Level Agreements) heutiger geschäftskritischer Anwendungen für HA und DR nicht erfüllen kann. Denn dies impliziert eine auf der Client-Seite erlebte Failover-Zeit von insgesamt 16 Minuten. Hierzu ein Auszug aus der SQL Server 2012 Online Dokumentation: Cons: If a cross-subnet failover occurs, the client recovery time could be 15 minutes or longer, depending on your HostRecordTTL setting and the setting of your cross-site DNS/AD replication schedule.    Wir sind hier an einem Punkt unserer Überlegungen angelangt, an dem sich erklärt, weshalb ich zuvor das "Windows was the God ..." Zitat verwendet habe. Die unbedingte Abhängigkeit zu Windows wird zunehmend zum Problem, da sie die Komplexität einer Microsoft-basierenden Lösung erhöht, anstelle sie zu reduzieren. Und Komplexität ist das Letzte, was sich CIOs heutzutage wünschen.  Zur Ehrenrettung des SQL Server 2012 und AlwaysOn muss man sagen, dass derart lange Failover-Zeiten kein unbedingtes "Muss" darstellen, sondern ein "Kann". Doch auch ein "Kann" kann im unpassenden Moment unvorhersehbare und kostspielige Folgen haben. Die Unabsehbarkeit ist wiederum Ursache vieler an der Implementierung beteiligten Komponenten und deren Abhängigkeiten, wie beispielsweise drei Cluster-Lösungen (zwei von Microsoft, eine 3rd Party Lösung). Wie man die Sache auch dreht und wendet, kommt man an diesem Fakt also nicht vorbei - ganz unabhängig von der Dauer einer Downtime oder Failover-Zeiten. Im Gegensatz zu AlwaysOn und der hier vorgestellten Version eines Stretch-Clusters, vermeidet eine entsprechende Oracle Implementierung eine derartige Komplexität, hervorgerufen duch multiple Abhängigkeiten. Den Unterschied machen Datenbank-integrierte Mechanismen, wie Fast Application Notification (FAN) und Fast Connection Failover (FCF). Für Oracle MAA Konfigurationen (Maximum Availability Architecture) sind Inter-Site Failover-Zeiten im Bereich von Sekunden keine Seltenheit. Wenn Sie dem Link zur Oracle MAA folgen, finden Sie außerdem eine Reihe an Customer Case Studies. Auch dies ist ein wichtiges Unterscheidungsmerkmal zu AlwaysOn, denn die Oracle Technologie hat sich bereits zigfach in höchst kritischen Umgebungen bewährt.   Availability Groups (Verfügbarkeitsgruppen) Die sogenannten Availability Groups (Verfügbarkeitsgruppen) sind - neben FCI - der weitere Baustein von AlwaysOn.   Hinweis: Bevor wir uns näher damit beschäftigen, sollten Sie sich noch einmal ins Gedächtnis rufen, dass eine SQL Server Datenbank nicht die gleiche Bedeutung besitzt, wie eine Oracle Datenbank, sondern eher einem Oracle Schema entspricht. So etwas wie die SQL Server Northwind Datenbank ist vergleichbar mit dem Oracle Scott Schema.   Eine Verfügbarkeitsgruppe setzt sich zusammen aus einem Set mehrerer Benutzer-Datenbanken, die im Falle eines Failover gemeinsam als Gruppe behandelt werden. Eine Verfügbarkeitsgruppe unterstützt ein Set an primären Datenbanken (primäres Replikat) und einem bis vier Sets von entsprechenden sekundären Datenbanken (sekundäre Replikate).       Es können jedoch nicht alle SQL Server Datenbanken einer AlwaysOn Verfügbarkeitsgruppe zugeordnet werden. Der SQL Server Spezialist Michael Otey zählt in seinem SQL Server Pro Artikel folgende Anforderungen auf: Verfügbarkeitsgruppen müssen mit Benutzer-Datenbanken erstellt werden. System-Datenbanken können nicht verwendet werden Die Datenbanken müssen sich im Read-Write Modus befinden. Read-Only Datenbanken werden nicht unterstützt Die Datenbanken in einer Verfügbarkeitsgruppe müssen Multiuser Datenbanken sein Sie dürfen nicht das AUTO_CLOSE Feature verwenden Sie müssen das Full Recovery Modell nutzen und es muss ein vollständiges Backup vorhanden sein Eine gegebene Datenbank kann sich nur in einer einzigen Verfügbarkeitsgruppe befinden und diese Datenbank düerfen nicht für Database Mirroring konfiguriert sein Microsoft empfiehl außerdem, dass der Verzeichnispfad einer Datenbank auf dem primären und sekundären Server identisch sein sollte Wie man sieht, eignen sich Verfügbarkeitsgruppen nicht, um HA und DR vollständig abzubilden. Die Unterscheidung zwischen der Instanzen-Ebene (FCI) und Datenbank-Ebene (Availability Groups) ist von hoher Bedeutung. Vor kurzem wurde mir gesagt, dass man mit den Verfügbarkeitsgruppen auf Shared Storage verzichten könne und dadurch Kosten spart. So weit so gut ... Man kann natürlich eine Installation rein mit Verfügbarkeitsgruppen und ohne FCI durchführen - aber man sollte sich dann darüber bewusst sein, was man dadurch alles nicht abgesichert hat - und dies wiederum für Desaster Recovery (DR) und SLAs (Service Level Agreements) bedeutet. Kurzum, um die Kombination aus beiden AlwaysOn Produkten und der damit verbundene Komplexität kommt man wohl in der Praxis nicht herum.    Availability Groups und WSFC AlwaysOn hängt von Windows Server Failover Clustering (WSFC) ab, um die aktuellen Rollen der Verfügbarkeitsreplikate einer Verfügbarkeitsgruppe zu überwachen und zu verwalten, und darüber zu entscheiden, wie ein Failover-Ereignis die Verfügbarkeitsreplikate betrifft. Das folgende Diagramm zeigt de Beziehung zwischen Verfügbarkeitsgruppen und WSFC:   Der Verfügbarkeitsmodus ist eine Eigenschaft jedes Verfügbarkeitsreplikats. Synychron und Asynchron können also gemischt werden: Availability Modus (Verfügbarkeitsmodus) Asynchroner Commit-Modus Primäres replikat schließt Transaktionen ohne Warten auf Sekundäres Synchroner Commit-Modus Primäres Replikat wartet auf Commit von sekundärem Replikat Failover Typen Automatic Manual Forced (mit möglichem Datenverlust) Synchroner Commit-Modus Geplanter, manueller Failover ohne Datenverlust Automatischer Failover ohne Datenverlust Asynchroner Commit-Modus Nur Forced, manueller Failover mit möglichem Datenverlust   Der SQL Server kennt keinen separaten Switchover Begriff wie in Oracle Data Guard. Für SQL Server werden alle Role Transitions als Failover bezeichnet. Tatsächlich unterstützt der SQL Server keinen Switchover für asynchrone Verbindungen. Es gibt nur die Form des Forced Failover mit möglichem Datenverlust. Eine ähnliche Fähigkeit wie der Switchover unter Oracle Data Guard ist so nicht gegeben.   SQL Sever FCI mit Availability Groups (Verfügbarkeitsgruppen) Neben den Verfügbarkeitsgruppen kann eine zweite Failover-Ebene eingerichtet werden, indem SQL Server FCI (auf Shared Storage) mit WSFC implementiert wird. Ein Verfügbarkeitesreplikat kann dann auf einer Standalone Instanz gehostet werden, oder einer FCI Instanz. Zum Verständnis: Die Verfügbarkeitsgruppen selbst benötigen kein Shared Storage. Diese Kombination kann verwendet werden für lokale HA auf Ebene der Instanz und DR auf Datenbank-Ebene durch Verfügbarkeitsgruppen. Das folgende Diagramm zeigt dieses Szenario:   Achtung! Hier handelt es sich nicht um ein Pendant zu Oracle RAC plus Data Guard, auch wenn das Bild diesen Eindruck vielleicht vermitteln mag - denn alle sekundären Knoten im FCI sind rein passiv. Es existiert außerdem eine weitere und ernsthafte Einschränkung: SQL Server Failover Cluster Instanzen (FCI) unterstützen nicht das automatische AlwaysOn Failover für Verfügbarkeitsgruppen. Jedes unter FCI gehostete Verfügbarkeitsreplikat kann nur für manuelles Failover konfiguriert werden.   Lesbare Sekundäre Replikate Ein oder mehrere Verfügbarkeitsreplikate in einer Verfügbarkeitsgruppe können für den lesenden Zugriff konfiguriert werden, wenn sie als sekundäres Replikat laufen. Dies ähnelt Oracle Active Data Guard, jedoch gibt es Einschränkungen. Alle Abfragen gegen die sekundäre Datenbank werden automatisch auf das Snapshot Isolation Level abgebildet. Es handelt sich dabei um eine Versionierung der Rows. Microsoft versuchte hiermit die Oracle MVRC (Multi Version Read Consistency) nachzustellen. Tatsächlich muss man die SQL Server Snapshot Isolation eher mit Oracle Flashback vergleichen. Bei der Implementierung des Snapshot Isolation Levels handelt sich um ein nachträglich aufgesetztes Feature und nicht um einen inhärenten Teil des Datenbank-Kernels, wie im Falle Oracle. (Ich werde hierzu in Kürze einen weiteren Blogbeitrag verfassen, wenn ich mich mit der neuen SQL Server 2012 Core Lizenzierung beschäftige.) Für die Praxis entstehen aus der Abbildung auf das Snapshot Isolation Level ernsthafte Restriktionen, derer man sich für den Betrieb in der Praxis bereits vorab bewusst sein sollte: Sollte auf der primären Datenbank eine aktive Transaktion zu dem Zeitpunkt existieren, wenn ein lesbares sekundäres Replikat in die Verfügbarkeitsgruppe aufgenommen wird, werden die Row-Versionen auf der korrespondierenden sekundären Datenbank nicht sofort vollständig verfügbar sein. Eine aktive Transaktion auf dem primären Replikat muss zuerst abgeschlossen (Commit oder Rollback) und dieser Transaktions-Record auf dem sekundären Replikat verarbeitet werden. Bis dahin ist das Isolation Level Mapping auf der sekundären Datenbank unvollständig und Abfragen sind temporär geblockt. Microsoft sagt dazu: "This is needed to guarantee that row versions are available on the secondary replica before executing the query under snapshot isolation as all isolation levels are implicitly mapped to snapshot isolation." (SQL Storage Engine Blog: AlwaysOn: I just enabled Readable Secondary but my query is blocked?)  Grundlegend bedeutet dies, dass ein aktives lesbares Replikat nicht in die Verfügbarkeitsgruppe aufgenommen werden kann, ohne das primäre Replikat vorübergehend stillzulegen. Da Leseoperationen auf das Snapshot Isolation Transaction Level abgebildet werden, kann die Bereinigung von Ghost Records auf dem primären Replikat durch Transaktionen auf einem oder mehreren sekundären Replikaten geblockt werden - z.B. durch eine lang laufende Abfrage auf dem sekundären Replikat. Diese Bereinigung wird auch blockiert, wenn die Verbindung zum sekundären Replikat abbricht oder der Datenaustausch unterbrochen wird. Auch die Log Truncation wird in diesem Zustant verhindert. Wenn dieser Zustand längere Zeit anhält, empfiehlt Microsoft das sekundäre Replikat aus der Verfügbarkeitsgruppe herauszunehmen - was ein ernsthaftes Downtime-Problem darstellt. Die Read-Only Workload auf den sekundären Replikaten kann eingehende DDL Änderungen blockieren. Obwohl die Leseoperationen aufgrund der Row-Versionierung keine Shared Locks halten, führen diese Operatioen zu Sch-S Locks (Schemastabilitätssperren). DDL-Änderungen durch Redo-Operationen können dadurch blockiert werden. Falls DDL aufgrund konkurrierender Lese-Workload blockiert wird und der Schwellenwert für 'Recovery Interval' (eine SQL Server Konfigurationsoption) überschritten wird, generiert der SQL Server das Ereignis sqlserver.lock_redo_blocked, welches Microsoft zum Kill der blockierenden Leser empfiehlt. Auf die Verfügbarkeit der Anwendung wird hierbei keinerlei Rücksicht genommen.   Keine dieser Einschränkungen existiert mit Oracle Active Data Guard.   Backups auf sekundären Replikaten  Über die sekundären Replikate können Backups (BACKUP DATABASE via Transact-SQL) nur als copy-only Backups einer vollständigen Datenbank, Dateien und Dateigruppen erstellt werden. Das Erstellen inkrementeller Backups ist nicht unterstützt, was ein ernsthafter Rückstand ist gegenüber der Backup-Unterstützung physikalischer Standbys unter Oracle Data Guard. Hinweis: Ein möglicher Workaround via Snapshots, bleibt ein Workaround. Eine weitere Einschränkung dieses Features gegenüber Oracle Data Guard besteht darin, dass das Backup eines sekundären Replikats nicht ausgeführt werden kann, wenn es nicht mit dem primären Replikat kommunizieren kann. Darüber hinaus muss das sekundäre Replikat synchronisiert sein oder sich in der Synchronisation befinden, um das Beackup auf dem sekundären Replikat erstellen zu können.   Vergleich von Microsoft AlwaysOn mit der Oracle MAA Ich komme wieder zurück auf die Eingangs erwähnte, mehrfach an mich gestellte Frage "Wann denn - und ob überhaupt - Oracle etwas Vergleichbares wie AlwaysOn bieten würde?" und meine damit verbundene (kurze) Irritation. Wenn Sie diesen Blogbeitrag bis hierher gelesen haben, dann kennen Sie jetzt meine darauf gegebene Antwort. Der eine oder andere Punkt traf dabei nicht immer auf Jeden zu, was auch nicht der tiefere Sinn und Zweck meiner Antwort war. Wenn beispielsweise kein Multi-Subnet mit im Spiel ist, sind alle diesbezüglichen Kritikpunkte zunächst obsolet. Was aber nicht bedeutet, dass sie nicht bereits morgen schon wieder zum Thema werden könnten (Sag niemals "Nie"). In manch anderes Fettnäpfchen tritt man wiederum nicht unbedingt in einer Testumgebung, sondern erst im laufenden Betrieb. Erst recht nicht dann, wenn man sich potenzieller Probleme nicht bewusst ist und keine dedizierten Tests startet. Und wer AlwaysOn erfolgreich positionieren möchte, wird auch gar kein Interesse daran haben, auf mögliche Schwachstellen und den besagten Teufel im Detail aufmerksam zu machen. Das ist keine Unterstellung - es ist nur menschlich. Außerdem ist es verständlich, dass man sich in erster Linie darauf konzentriert "was geht" und "was gut läuft", anstelle auf das "was zu Problemen führen kann" oder "nicht funktioniert". Wer will schon der Miesepeter sein? Für mich selbst gesprochen, kann ich nur sagen, dass ich lieber vorab von allen möglichen Einschränkungen wissen möchte, anstelle sie dann nach einer kurzen Zeit der heilen Welt schmerzhaft am eigenen Leib erfahren zu müssen. Ich bin davon überzeugt, dass es Ihnen nicht anders geht. Nachfolgend deshalb eine Zusammenfassung all jener Punkte, die ich im Vergleich zur Oracle MAA (Maximum Availability Architecture) als unbedingt Erwähnenswert betrachte, falls man eine Evaluierung von Microsoft AlwaysOn in Betracht zieht. 1. AlwaysOn ist eine komplexe Technologie Der SQL Server AlwaysOn Stack ist zusammengesetzt aus drei verschiedenen Technlogien: Windows Server Failover Clustering (WSFC) SQL Server Failover Cluster Instances (FCI) SQL Server Availability Groups (Verfügbarkeitsgruppen) Man kann eine derartige Lösung nicht als nahtlos bezeichnen, wofür auch die vielen von Microsoft dargestellten Einschränkungen sprechen. Während sich frühere SQL Server Versionen in Richtung eigener HA/DR Technologien entwickelten (wie Database Mirroring), empfiehlt Microsoft nun die Migration. Doch weshalb dieser Schwenk? Er führt nicht zu einem konsisten und robusten Angebot an HA/DR Technologie für geschäftskritische Umgebungen.  Liegt die Antwort in meiner These begründet, nach der "Windows was the God ..." noch immer gilt und man die Nachteile der allzu engen Kopplung mit Windows nicht sehen möchte? Entscheiden Sie selbst ... 2. Failover Cluster Instanzen - Kein RAC-Pendant Die SQL Server und Windows Server Clustering Technologie basiert noch immer auf dem veralteten Aktiv-Passiv Modell und führt zu einer Verschwendung von Systemressourcen. In einer Betrachtung von lediglich zwei Knoten erschließt sich auf Anhieb noch nicht der volle Mehrwert eines Aktiv-Aktiv Clusters (wie den Real Application Clusters), wie er von Oracle bereits vor zehn Jahren entwickelt wurde. Doch kennt man die Vorzüge der Skalierbarkeit durch einfaches Hinzufügen weiterer Cluster-Knoten, die dann alle gemeinsam als ein einziges logisches System zusammenarbeiten, versteht man was hinter dem Motto "Pay-as-you-Grow" steckt. In einem Aktiv-Aktiv Cluster geht es zwar auch um Hochverfügbarkeit - und ein Failover erfolgt zudem schneller, als in einem Aktiv-Passiv Modell - aber es geht eben nicht nur darum. An dieser Stelle sei darauf hingewiesen, dass die Oracle 11g Standard Edition bereits die Nutzung von Oracle RAC bis zu vier Sockets kostenfrei beinhaltet. Möchten Sie dazu Windows nutzen, benötigen Sie keine Windows Server Enterprise Edition, da Oracle 11g die eigene Clusterware liefert. Sie kommen in den Genuss von Hochverfügbarkeit und Skalierbarkeit und können dazu die günstigere Windows Server Standard Edition nutzen. 3. SQL Server Multi-Subnet Clustering - Abhängigkeit zu 3rd Party Storage Mirroring  Die SQL Server Multi-Subnet Clustering Architektur unterstützt den Aufbau eines Stretch Clusters, basiert dabei aber auf dem Aktiv-Passiv Modell. Das eigentlich Problematische ist jedoch, dass man sich zur Absicherung der Datenbank auf 3rd Party Storage Mirroring Technologie verlässt, ohne Integration zwischen dem Windows Server Failover Clustering (WSFC) und der darunterliegenden Mirroring Technologie. Wenn nun im Cluster ein Failover auf Instanzen-Ebene erfolgt, existiert keine Koordination mit einem möglichen Failover auf Ebene des Storage-Array. 4. Availability Groups (Verfügbarkeitsgruppen) - Vier, oder doch nur Zwei? Ein primäres Replikat erlaubt bis zu vier sekundäre Replikate innerhalb einer Verfügbarkeitsgruppe, jedoch nur zwei im Synchronen Commit Modus. Während dies zwar einen Vorteil gegenüber dem stringenten 1:1 Modell unter Database Mirroring darstellt, fällt der SQL Server 2012 damit immer noch weiter zurück hinter Oracle Data Guard mit bis zu 30 direkten Stanbdy Zielen - und vielen weiteren durch kaskadierende Ziele möglichen. Damit eignet sich Oracle Active Data Guard auch für die Bereitstellung einer Reader-Farm Skalierbarkeit für Internet-basierende Unternehmen. Mit AwaysOn Verfügbarkeitsgruppen ist dies nicht möglich. 5. Availability Groups (Verfügbarkeitsgruppen) - kein asynchrones Switchover  Die Technologie der Verfügbarkeitsgruppen wird auch als geeignetes Mittel für administrative Aufgaben positioniert - wie Upgrades oder Wartungsarbeiten. Man muss sich jedoch einem gravierendem Defizit bewusst sein: Im asynchronen Verfügbarkeitsmodus besteht die einzige Möglichkeit für Role Transition im Forced Failover mit Datenverlust! Um den Verlust von Daten durch geplante Wartungsarbeiten zu vermeiden, muss man den synchronen Verfügbarkeitsmodus konfigurieren, was jedoch ernstzunehmende Auswirkungen auf WAN Deployments nach sich zieht. Spinnt man diesen Gedanken zu Ende, kommt man zu dem Schluss, dass die Technologie der Verfügbarkeitsgruppen für geplante Wartungsarbeiten in einem derartigen Umfeld nicht effektiv genutzt werden kann. 6. Automatisches Failover - Nicht immer möglich Sowohl die SQL Server FCI, als auch Verfügbarkeitsgruppen unterstützen automatisches Failover. Möchte man diese jedoch kombinieren, wird das Ergebnis kein automatisches Failover sein. Denn ihr Zusammentreffen im Failover-Fall führt zu Race Conditions (Wettlaufsituationen), weshalb diese Konfiguration nicht länger das automatische Failover zu einem Replikat in einer Verfügbarkeitsgruppe erlaubt. Auch hier bestätigt sich wieder die tiefere Problematik von AlwaysOn, mit einer Zusammensetzung aus unterschiedlichen Technologien und der Abhängigkeit zu Windows. 7. Problematische RTO (Recovery Time Objective) Microsoft postioniert die SQL Server Multi-Subnet Clustering Architektur als brauchbare HA/DR Architektur. Bedenkt man jedoch die Problematik im Zusammenhang mit DNS Replikation und den möglichen langen Wartezeiten auf Client-Seite von bis zu 16 Minuten, sind strenge RTO Anforderungen (Recovery Time Objectives) nicht erfüllbar. Im Gegensatz zu Oracle besitzt der SQL Server keine Datenbank-integrierten Technologien, wie Oracle Fast Application Notification (FAN) oder Oracle Fast Connection Failover (FCF). 8. Problematische RPO (Recovery Point Objective) SQL Server ermöglicht Forced Failover (erzwungenes Failover), bietet jedoch keine Möglichkeit zur automatischen Übertragung der letzten Datenbits von einem alten zu einem neuen primären Replikat, wenn der Verfügbarkeitsmodus asynchron war. Oracle Data Guard hingegen bietet diese Unterstützung durch das Flush Redo Feature. Dies sichert "Zero Data Loss" und beste RPO auch in erzwungenen Failover-Situationen. 9. Lesbare Sekundäre Replikate mit Einschränkungen Aufgrund des Snapshot Isolation Transaction Level für lesbare sekundäre Replikate, besitzen diese Einschränkungen mit Auswirkung auf die primäre Datenbank. Die Bereinigung von Ghost Records auf der primären Datenbank, wird beeinflusst von lang laufenden Abfragen auf der lesabaren sekundären Datenbank. Die lesbare sekundäre Datenbank kann nicht in die Verfügbarkeitsgruppe aufgenommen werden, wenn es aktive Transaktionen auf der primären Datenbank gibt. Zusätzlich können DLL Änderungen auf der primären Datenbank durch Abfragen auf der sekundären blockiert werden. Und imkrementelle Backups werden hier nicht unterstützt.   Keine dieser Restriktionen existiert unter Oracle Data Guard.

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  • Learning AngularJS by Example – The Customer Manager Application

    - by dwahlin
    I’m always tinkering around with different ideas and toward the beginning of 2013 decided to build a sample application using AngularJS that I call Customer Manager. It’s not exactly the most creative name or concept, but I wanted to build something that highlighted a lot of the different features offered by AngularJS and how they could be used together to build a full-featured app. One of the goals of the application was to ensure that it was approachable by people new to Angular since I’ve never found overly complex applications great for learning new concepts. The application initially started out small and was used in my AngularJS in 60-ish Minutes video on YouTube but has gradually had more and more features added to it and will continue to be enhanced over time. It’ll be used in a new “end-to-end” training course my company is working on for AngularjS as well as in some video courses that will be coming out. Here’s a quick look at what the application home page looks like: In this post I’m going to provide an overview about how the application is organized, back-end options that are available, and some of the features it demonstrates. I’ve already written about some of the features so if you’re interested check out the following posts: Building an AngularJS Modal Service Building a Custom AngularJS Unique Value Directive Using an AngularJS Factory to Interact with a RESTful Service Application Structure The structure of the application is shown to the right. The  homepage is index.html and is located at the root of the application folder. It defines where application views will be loaded using the ng-view directive and includes script references to AngularJS, AngularJS routing and animation scripts, plus a few others located in the Scripts folder and to custom application scripts located in the app folder. The app folder contains all of the key scripts used in the application. There are several techniques that can be used for organizing script files but after experimenting with several of them I decided that I prefer things in folders such as controllers, views, services, etc. Doing that helps me find things a lot faster and allows me to categorize files (such as controllers) by functionality. My recommendation is to go with whatever works best for you. Anyone who says, “You’re doing it wrong!” should be ignored. Contrary to what some people think, there is no “one right way” to organize scripts and other files. As long as the scripts make it down to the client properly (you’ll likely minify and concatenate them anyway to reduce bandwidth and minimize HTTP calls), the way you organize them is completely up to you. Here’s what I ended up doing for this application: Animation code for some custom animations is located in the animations folder. In addition to AngularJS animations (which are defined using CSS in Content/animations.css), it also animates the initial customer data load using a 3rd party script called GreenSock. Controllers are located in the controllers folder. Some of the controllers are placed in subfolders based upon the their functionality while others are placed at the root of the controllers folder since they’re more generic:   The directives folder contains the custom directives created for the application. The filters folder contains the custom filters created for the application that filter city/state and product information. The partials folder contains partial views. This includes things like modal dialogs used in the application. The services folder contains AngularJS factories and services used for various purposes in the application. Most of the scripts in this folder provide data functionality. The views folder contains the different views used in the application. Like the controllers folder, the views are organized into subfolders based on their functionality:   Back-End Services The Customer Manager application (grab it from Github) provides two different options on the back-end including ASP.NET Web API and Node.js. The ASP.NET Web API back-end uses Entity Framework for data access and stores data in SQL Server (LocalDb). The other option on the back-end is Node.js, Express, and MongoDB.   Using the ASP.NET Web API Back-End To run the application using ASP.NET Web API/SQL Server back-end open the .sln file at the root of the project in Visual Studio 2012 or higher (the free Express 2013 for Web version is fine). Press F5 and a browser will automatically launch and display the application. Using the Node.js Back-End To run the application using the Node.js/MongoDB back-end follow these steps: In the CustomerManager directory execute 'npm install' to install Express, MongoDB and Mongoose (package.json). Load sample data into MongoDB by performing the following steps: Execute 'mongod' to start the MongoDB daemon Navigate to the CustomerManager directory (the one that has initMongoCustData.js in it) then execute 'mongo' to start the MongoDB shell Enter the following in the mongo shell to load the seed files that handle seeding the database with initial data: use custmgr load("initMongoCustData.js") load("initMongoSettingsData.js") load("initMongoStateData.js") Start the Node/Express server by navigating to the CustomerManager/server directory and executing 'node app.js' View the application at http://localhost:3000 in your browser. Key Features The Customer Manager application certainly doesn’t cover every feature provided by AngularJS (as mentioned the intent was to keep it as simple as possible) but does provide insight into several key areas: Using factories and services as re-useable data services (see the app/services folder) Creating custom directives (see the app/directives folder) Custom paging (see app/views/customers/customers.html and app/controllers/customers/customersController.js) Custom filters (see app/filters) Showing custom modal dialogs with a re-useable service (see app/services/modalService.js) Making Ajax calls using a factory (see app/services/customersService.js) Using Breeze to retrieve and work with data (see app/services/customersBreezeService.js). Switch the application to use the Breeze factory by opening app/services.config.js and changing the useBreeze property to true. Intercepting HTTP requests to display a custom overlay during Ajax calls (see app/directives/wcOverlay.js) Custom animations using the GreenSock library (see app/animations/listAnimations.js) Creating custom AngularJS animations using CSS (see Content/animations.css) JavaScript patterns for defining controllers, services/factories, directives, filters, and more (see any JavaScript file in the app folder) Card View and List View display of data (see app/views/customers/customers.html and app/controllers/customers/customersController.js) Using AngularJS validation functionality (see app/views/customerEdit.html, app/controllers/customerEditController.js, and app/directives/wcUnique.js) More… Conclusion I’ll be enhancing the application even more over time and welcome contributions as well. Tony Quinn contributed the initial Node.js/MongoDB code which is very cool to have as a back-end option. Access the standard application here and a version that has custom routing in it here. Additional information about the custom routing can be found in this post.

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