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• ORDER BY job failed in the Pig script while running EmbeddedPig using Java

  - by C.c. Huang

  I have this following pig script, which works perfectly using grunt shell (stored the results to HDFS without any issues); however, the last job (ORDER BY) failed if I ran the same script using Java EmbeddedPig. If I replace the ORDER BY job by others, such as GROUP or FOREACH GENERATE, the whole script then succeeded in Java EmbeddedPig. So I think it's the ORDER BY which causes the issue. Anyone has any experience with this? Any help would be appreciated! The Pig script: REGISTER pig-udf-0.0.1-SNAPSHOT.jar; user_similarity = LOAD '/tmp/sample-sim-score-results-31/part-r-00000' USING PigStorage('\t') AS (user_id: chararray, sim_user_id: chararray, basic_sim_score: float, alt_sim_score: float); simplified_user_similarity = FOREACH user_similarity GENERATE $0 AS user_id, $1 AS sim_user_id, $2 AS sim_score; grouped_user_similarity = GROUP simplified_user_similarity BY user_id; ordered_user_similarity = FOREACH grouped_user_similarity { sorted = ORDER simplified_user_similarity BY sim_score DESC; top = LIMIT sorted 10; GENERATE group, top; }; top_influencers = FOREACH ordered_user_similarity GENERATE com.aol.grapevine.similarity.pig.udf.AssignPointsToTopInfluencer($1, 10); all_influence_scores = FOREACH top_influencers GENERATE FLATTEN($0); grouped_influence_scores = GROUP all_influence_scores BY bag_of_topSimUserTuples::user_id; influence_scores = FOREACH grouped_influence_scores GENERATE group AS user_id, SUM(all_influence_scores.bag_of_topSimUserTuples::points) AS influence_score; ordered_influence_scores = ORDER influence_scores BY influence_score DESC; STORE ordered_influence_scores INTO '/tmp/cc-test-results-1' USING PigStorage(); The error log from Pig: 12/04/05 10:00:56 INFO pigstats.ScriptState: Pig script settings are added to the job 12/04/05 10:00:56 INFO mapReduceLayer.JobControlCompiler: mapred.job.reduce.markreset.buffer.percent is not set, set to default 0.3 12/04/05 10:00:58 INFO mapReduceLayer.JobControlCompiler: Setting up single store job 12/04/05 10:00:58 INFO jvm.JvmMetrics: Cannot initialize JVM Metrics with processName=JobTracker, sessionId= - already initialized 12/04/05 10:00:58 INFO mapReduceLayer.MapReduceLauncher: 1 map-reduce job(s) waiting for submission. 12/04/05 10:00:58 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same. 12/04/05 10:00:58 INFO input.FileInputFormat: Total input paths to process : 1 12/04/05 10:00:58 INFO util.MapRedUtil: Total input paths to process : 1 12/04/05 10:00:58 INFO util.MapRedUtil: Total input paths (combined) to process : 1 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating tmp-1546565755 in /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134-work-6955502337234509704 with rwxr-xr-x 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Cached hdfs://localhost/tmp/temp1725960134/tmp-1546565755#pigsample_854728855_1333645258470 as /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Cached hdfs://localhost/tmp/temp1725960134/tmp-1546565755#pigsample_854728855_1333645258470 as /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 12/04/05 10:00:58 WARN mapred.LocalJobRunner: LocalJobRunner does not support symlinking into current working dir. 12/04/05 10:00:58 INFO mapred.TaskRunner: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/pigsample_854728855_1333645258470 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.jar.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.jar.crc 12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.split.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.split.crc 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.splitmetainfo.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.splitmetainfo.crc 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.xml.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.xml.crc 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.jar <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.jar 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.split <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.split 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.splitmetainfo <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.splitmetainfo 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.xml <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.xml 12/04/05 10:00:59 INFO mapred.Task: Using ResourceCalculatorPlugin : null 12/04/05 10:00:59 INFO mapred.MapTask: io.sort.mb = 100 12/04/05 10:00:59 INFO mapred.MapTask: data buffer = 79691776/99614720 12/04/05 10:00:59 INFO mapred.MapTask: record buffer = 262144/327680 12/04/05 10:00:59 WARN mapred.LocalJobRunner: job_local_0004 java.lang.RuntimeException: org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/Users/cchuang/workspace/grapevine-rec/pigsample_854728855_1333645258470 at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.partitioners.WeightedRangePartitioner.setConf(WeightedRangePartitioner.java:139) at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:62) at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:117) at org.apache.hadoop.mapred.MapTask$NewOutputCollector.<init>(MapTask.java:560) at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:639) at org.apache.hadoop.mapred.MapTask.run(MapTask.java:323) at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:210) Caused by: org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/Users/cchuang/workspace/grapevine-rec/pigsample_854728855_1333645258470 at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(FileInputFormat.java:231) at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigFileInputFormat.listStatus(PigFileInputFormat.java:37) at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.getSplits(FileInputFormat.java:248) at org.apache.pig.impl.io.ReadToEndLoader.init(ReadToEndLoader.java:153) at org.apache.pig.impl.io.ReadToEndLoader.<init>(ReadToEndLoader.java:115) at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.partitioners.WeightedRangePartitioner.setConf(WeightedRangePartitioner.java:112) ... 6 more 12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Deleted path /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 12/04/05 10:00:59 INFO mapReduceLayer.MapReduceLauncher: HadoopJobId: job_local_0004 12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: job job_local_0004 has failed! Stop running all dependent jobs 12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: 100% complete 12/04/05 10:01:04 ERROR pigstats.PigStatsUtil: 1 map reduce job(s) failed! 12/04/05 10:01:04 INFO pigstats.PigStats: Script Statistics: HadoopVersion PigVersion UserId StartedAt FinishedAt Features 0.20.2-cdh3u3 0.8.1-cdh3u3 cchuang 2012-04-05 10:00:34 2012-04-05 10:01:04 GROUP_BY,ORDER_BY Some jobs have failed! Stop running all dependent jobs Job Stats (time in seconds): JobId Maps Reduces MaxMapTime MinMapTIme AvgMapTime MaxReduceTime MinReduceTime AvgReduceTime Alias Feature Outputs job_local_0001 0 0 0 0 0 0 0 0 all_influence_scores,grouped_user_similarity,simplified_user_similarity,user_similarity GROUP_BY job_local_0002 0 0 0 0 0 0 0 0 grouped_influence_scores,influence_scores GROUP_BY,COMBINER job_local_0003 0 0 0 0 0 0 0 0 ordered_influence_scores SAMPLER Failed Jobs: JobId Alias Feature Message Outputs job_local_0004 ordered_influence_scores ORDER_BY Message: Job failed! Error - NA /tmp/cc-test-results-1, Input(s): Successfully read 0 records from: "/tmp/sample-sim-score-results-31/part-r-00000" Output(s): Failed to produce result in "/tmp/cc-test-results-1" Counters: Total records written : 0 Total bytes written : 0 Spillable Memory Manager spill count : 0 Total bags proactively spilled: 0 Total records proactively spilled: 0 Job DAG: job_local_0001 -> job_local_0002, job_local_0002 -> job_local_0003, job_local_0003 -> job_local_0004, job_local_0004 12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: Some jobs have failed! Stop running all dependent jobs

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• Oracle's Cloud Strategie nach der OOW 2012

  - by Manuel Hossfeld

  Auf der diesjährigen Oracle Open World war „die Cloud“ nicht nur ein vielbenutztes Buzzword, sondern auch Anlass für einige interessante Ankündigungen. Wer keine Zeit oder Muße hatte, sich die entsprechenden Keynotes von Larry Ellison und Thomas Kurian anzuhören, erfährt in diesem Artikel die wesentlichen Änderungen. Die erste Neuerung: Oracle wird in Zukunft alle drei „Sorten“ bzw. „Ebenen“ von Cloud Computing anbieten: SaaS (Software as a Service) – die Bereitstellung von kompletten Fachanwendungen z.B. aus der eBusiness Suite in Form eines Mietmodells - gab es schon länger. Abgesehen von der Tatsache, dass hier zusätzliche/neuere Komponenten und Module der durch die letzten Zukäufe von Oracle noch breiter gewordenen Palette angeboten werden, ändert sich am Prinzip nichts. Bei PaaS (Plattform as a Service) sind vor allem die beiden bereits letztes Jahr angekündigten Dienste „Database Service“ (basierend auf APEX) und „Java Service“ (basierend auf Weblogic) zu nennen, für die nun auch konkrete Pakete und Preise (ca.175$ bis 2000$/Monat) sowie die Möglichkeit zur Anmeldung auf http://cloud.oracle.com vorliegen. Interessanterweise gehört auch ein sog. „Social Service“ in diese Schicht, mit der Oracle Kunden ihre Anwendungen in Zukunft auf standardisierte Weise durch Social Networking Funktionalität wie z.B. Microblogging erweitern können.Ebenso neu angekündigt wurde ein "Developer Service", welcher z.B. Sourcecode-Verwaltung durch GIT Repositories sowie Wikis und Issue Tracking bereit stellen soll. Die dort mittels JDeveloper, Netbeans oder Eclipse erstellten Applikationen können dann nahtlos innerhalb kürzester Zeit in den Java Service deployed werden. Komplett neu und für einige sicher überraschend ist hingegen der Bereich IaaS (Infrastructure as a Service) – Hier geht es um die Bereitstellung von Basis-Infrastrukturkomponenten wie Storage, Rechenleistung (letztlich also Betriebssysteme / VMs) und Messaging / Queueing. Genaue Details oder Preise zu den IaaS Angeboten sind noch nicht bekannt, aber zumindest zu den Storage- und Messaging Services können grundlegende Daten bereits auf http://cloud.oracle.com eingesehen werden Die zweite Neuerung: Kunden können in Zukunft als Alternative zum Betrieb der o.g. „Oracle Cloud“, diese auch komplett hinter ihrer eigenen Firewall aufbauen lassen. Mit anderen Worten: Oracle baut und betreibt bei diesem als „Oracle Private Cloud“ bezeichneten Angebot alle Komponenten selbst – die Daten verlassen aber niemals das Gebäude des Kunden. Letzteres ist gerade bei uns im Datenschutz-sensiblen Deutschland ein wichtiger Aspekt. Da die verwendeten Komponenten in beiden Fällen die gleichen sind, ist auch ein „Umziehen“ oder Erweitern der Private Cloud in die Public Cloud (oder zurück) ohne Änderungen an den Anwendungen möglich. Der Möglichkeit einer "Hybrid Cloud", bei der Teile einer Anwendung hinter der eigenen Firewall, andere Teile aber in der Oracle Cloud laufen, wird damit Realität.

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• jQuery .die isnt killing an attached event?

  - by adam

  Hi I've just started experimenting with .live and .die and having some great results but one thing isn't working. I've been tinkering with firebugs console to try out my written code live to see if i can figure out the reason why .die isn't killing off an attached event. First if i do this //attach ajax submission $('a[href$=edit]').live("click", function(event) { $.get($(this).attr("href"), null, null); return false; }); Then as expected when I click on a link the ajax fires off and my server side code injects a form for inline editing. But sometimes I want to disable this behaviour and also make the link unclickable so I do the following //unbind ajax form creation when we click on a link, then disable its semantic behaviour $('a[href$=edit]').die("click").click( function(){ return false; } ); which works but if then try to remove this and restore that ajax goodness with the code below it doesn't work, Instead the link remains unclickable. I cant figure out why? Can anyone help? //remove any previous events from the links $('a[href$=edit]').die(); //attach ajax submission $('a[href$=edit]').live("click", function(event) { $.get($(this).attr("href"), null, null); return false; });

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• How to tune down the Hyperic built-in postgresql database for a small setup

  - by Svish

  We are testing out Hyperic 4.5.1 in a quite small environment for now. Currently there are just 1-5 agents and there probably won't be any more than 10-15. When I run ps ax there are 20(!) postgres processes running. For a small setup like this, that can't be necessary, can it? I'm a software developer and don't have much experience with setting up servers and such though, so don't really know. Either way, what settings are appropriate for a small Hyperic setup like this? Current, default and untouched configuration file, hqdb/data/postgresql.conf: # ----------------------------- # PostgreSQL configuration file # ----------------------------- # # This file consists of lines of the form: # # name = value # # (The '=' is optional.) White space may be used. Comments are introduced # with '#' anywhere on a line. The complete list of option names and # allowed values can be found in the PostgreSQL documentation. The # commented-out settings shown in this file represent the default values. # # Please note that re-commenting a setting is NOT sufficient to revert it # to the default value, unless you restart the server. # # Any option can also be given as a command line switch to the server, # e.g., 'postgres -c log_connections=on'. Some options can be changed at # run-time with the 'SET' SQL command. # # This file is read on server startup and when the server receives a # SIGHUP. If you edit the file on a running system, you have to SIGHUP the # server for the changes to take effect, or use "pg_ctl reload". Some # settings, which are marked below, require a server shutdown and restart # to take effect. # # Memory units: kB = kilobytes MB = megabytes GB = gigabytes # Time units: ms = milliseconds s = seconds min = minutes h = hours d = days #--------------------------------------------------------------------------- # FILE LOCATIONS #--------------------------------------------------------------------------- # The default values of these variables are driven from the -D command line # switch or PGDATA environment variable, represented here as ConfigDir. #data_directory = 'ConfigDir' # use data in another directory # (change requires restart) #hba_file = 'ConfigDir/pg_hba.conf' # host-based authentication file # (change requires restart) #ident_file = 'ConfigDir/pg_ident.conf' # ident configuration file # (change requires restart) # If external_pid_file is not explicitly set, no extra PID file is written. #external_pid_file = '(none)' # write an extra PID file # (change requires restart) #--------------------------------------------------------------------------- # CONNECTIONS AND AUTHENTICATION #--------------------------------------------------------------------------- # - Connection Settings - #listen_addresses = 'localhost' # what IP address(es) to listen on; # comma-separated list of addresses; # defaults to 'localhost', '*' = all # (change requires restart) port = 9432 # (change requires restart) max_connections = 100 # (change requires restart) # Note: increasing max_connections costs ~400 bytes of shared memory per # connection slot, plus lock space (see max_locks_per_transaction). You # might also need to raise shared_buffers to support more connections. #superuser_reserved_connections = 3 # (change requires restart) #unix_socket_directory = '' # (change requires restart) #unix_socket_group = '' # (change requires restart) #unix_socket_permissions = 0777 # octal # (change requires restart) #bonjour_name = '' # defaults to the computer name # (change requires restart) # - Security & Authentication - #authentication_timeout = 1min # 1s-600s #ssl = off # (change requires restart) #password_encryption = on #db_user_namespace = off # Kerberos #krb_server_keyfile = '' # (change requires restart) #krb_srvname = 'postgres' # (change requires restart) #krb_server_hostname = '' # empty string matches any keytab entry # (change requires restart) #krb_caseins_users = off # (change requires restart) # - TCP Keepalives - # see 'man 7 tcp' for details #tcp_keepalives_idle = 0 # TCP_KEEPIDLE, in seconds; # 0 selects the system default #tcp_keepalives_interval = 0 # TCP_KEEPINTVL, in seconds; # 0 selects the system default #tcp_keepalives_count = 0 # TCP_KEEPCNT; # 0 selects the system default #--------------------------------------------------------------------------- # RESOURCE USAGE (except WAL) #--------------------------------------------------------------------------- # - Memory - shared_buffers = 64MB # min 128kB or max_connections*16kB # (change requires restart) #temp_buffers = 8MB # min 800kB #max_prepared_transactions = 5 # can be 0 or more # (change requires restart) # Note: increasing max_prepared_transactions costs ~600 bytes of shared memory # per transaction slot, plus lock space (see max_locks_per_transaction). work_mem = 2MB # min 64kB maintenance_work_mem = 32MB # min 1MB #max_stack_depth = 2MB # min 100kB # - Free Space Map - max_fsm_pages = 204800 # min max_fsm_relations*16, 6 bytes each # (change requires restart) #max_fsm_relations = 1000 # min 100, ~70 bytes each # (change requires restart) # - Kernel Resource Usage - #max_files_per_process = 1000 # min 25 # (change requires restart) #shared_preload_libraries = '' # (change requires restart) # - Cost-Based Vacuum Delay - #vacuum_cost_delay = 0 # 0-1000 milliseconds #vacuum_cost_page_hit = 1 # 0-10000 credits #vacuum_cost_page_miss = 10 # 0-10000 credits #vacuum_cost_page_dirty = 20 # 0-10000 credits #vacuum_cost_limit = 200 # 0-10000 credits # - Background writer - #bgwriter_delay = 200ms # 10-10000ms between rounds #bgwriter_lru_percent = 1.0 # 0-100% of LRU buffers scanned/round #bgwriter_lru_maxpages = 5 # 0-1000 buffers max written/round #bgwriter_all_percent = 0.333 # 0-100% of all buffers scanned/round #bgwriter_all_maxpages = 5 # 0-1000 buffers max written/round #--------------------------------------------------------------------------- # WRITE AHEAD LOG #--------------------------------------------------------------------------- # - Settings - fsync = on # turns forced synchronization on or off #wal_sync_method = fsync # the default is the first option # supported by the operating system: # open_datasync # fdatasync # fsync # fsync_writethrough # open_sync #full_page_writes = on # recover from partial page writes #wal_buffers = 64kB # min 32kB # (change requires restart) commit_delay = 100000 # range 0-100000, in microseconds #commit_siblings = 5 # range 1-1000 # - Checkpoints - checkpoint_segments = 10 # in logfile segments, min 1, 16MB each #checkpoint_timeout = 5min # range 30s-1h #checkpoint_warning = 30s # 0 is off # - Archiving - #archive_command = '' # command to use to archive a logfile segment #archive_timeout = 0 # force a logfile segment switch after this # many seconds; 0 is off #--------------------------------------------------------------------------- # QUERY TUNING #--------------------------------------------------------------------------- # - Planner Method Configuration - #enable_bitmapscan = on #enable_hashagg = on #enable_hashjoin = on #enable_indexscan = on #enable_mergejoin = on #enable_nestloop = on #enable_seqscan = on #enable_sort = on #enable_tidscan = on # - Planner Cost Constants - #seq_page_cost = 1.0 # measured on an arbitrary scale #random_page_cost = 4.0 # same scale as above #cpu_tuple_cost = 0.01 # same scale as above #cpu_index_tuple_cost = 0.005 # same scale as above #cpu_operator_cost = 0.0025 # same scale as above #effective_cache_size = 128MB # - Genetic Query Optimizer - #geqo = on #geqo_threshold = 12 #geqo_effort = 5 # range 1-10 #geqo_pool_size = 0 # selects default based on effort #geqo_generations = 0 # selects default based on effort #geqo_selection_bias = 2.0 # range 1.5-2.0 # - Other Planner Options - #default_statistics_target = 10 # range 1-1000 #constraint_exclusion = off #from_collapse_limit = 8 #join_collapse_limit = 8 # 1 disables collapsing of explicit # JOINs #--------------------------------------------------------------------------- # ERROR REPORTING AND LOGGING #--------------------------------------------------------------------------- # - Where to Log - log_destination = 'stderr' # Valid values are combinations of # stderr, syslog and eventlog, # depending on platform. # This is used when logging to stderr: redirect_stderr = on # Enable capturing of stderr into log # files # (change requires restart) # These are only used if redirect_stderr is on: log_directory = '../../logs' # Directory where log files are written # Can be absolute or relative to PGDATA log_filename = 'hqdb-%Y-%m-%d.log' # Log file name pattern. # Can include strftime() escapes #log_truncate_on_rotation = off # If on, any existing log file of the same # name as the new log file will be # truncated rather than appended to. But # such truncation only occurs on # time-driven rotation, not on restarts # or size-driven rotation. Default is # off, meaning append to existing files # in all cases. log_rotation_age = 1d # Automatic rotation of logfiles will # happen after that time. 0 to # disable. #log_rotation_size = 10MB # Automatic rotation of logfiles will # happen after that much log # output. 0 to disable. # These are relevant when logging to syslog: #syslog_facility = 'LOCAL0' #syslog_ident = 'postgres' # - When to Log - #client_min_messages = notice # Values, in order of decreasing detail: # debug5 # debug4 # debug3 # debug2 # debug1 # log # notice # warning # error #log_min_messages = notice # Values, in order of decreasing detail: # debug5 # debug4 # debug3 # debug2 # debug1 # info # notice # warning # error # log # fatal # panic #log_error_verbosity = default # terse, default, or verbose messages #log_min_error_statement = error # Values in order of increasing severity: # debug5 # debug4 # debug3 # debug2 # debug1 # info # notice # warning # error # fatal # panic (effectively off) log_min_duration_statement = 10000 # -1 is disabled, 0 logs all statements # and their durations. #silent_mode = off # DO NOT USE without syslog or # redirect_stderr # (change requires restart) # - What to Log - #debug_print_parse = off #debug_print_rewritten = off #debug_print_plan = off #debug_pretty_print = off #log_connections = off #log_disconnections = off #log_duration = off #log_line_prefix = '' # Special values: # %u = user name # %d = database name # %r = remote host and port # %h = remote host # %p = PID # %t = timestamp (no milliseconds) # %m = timestamp with milliseconds # %i = command tag # %c = session id # %l = session line number # %s = session start timestamp # %x = transaction id # %q = stop here in non-session # processes # %% = '%' # e.g. '<%u%%%d> ' #log_statement = 'none' # none, ddl, mod, all #log_hostname = off #--------------------------------------------------------------------------- # RUNTIME STATISTICS #--------------------------------------------------------------------------- # - Query/Index Statistics Collector - #stats_command_string = on #update_process_title = on stats_start_collector = on # needed for block or row stats # (change requires restart) stats_block_level = on stats_row_level = on stats_reset_on_server_start = off # (change requires restart) # - Statistics Monitoring - #log_parser_stats = off #log_planner_stats = off #log_executor_stats = off #log_statement_stats = off #--------------------------------------------------------------------------- # AUTOVACUUM PARAMETERS #--------------------------------------------------------------------------- #autovacuum = off # enable autovacuum subprocess? # 'on' requires stats_start_collector # and stats_row_level to also be on #autovacuum_naptime = 1min # time between autovacuum runs #autovacuum_vacuum_threshold = 500 # min # of tuple updates before # vacuum #autovacuum_analyze_threshold = 250 # min # of tuple updates before # analyze #autovacuum_vacuum_scale_factor = 0.2 # fraction of rel size before # vacuum #autovacuum_analyze_scale_factor = 0.1 # fraction of rel size before # analyze #autovacuum_freeze_max_age = 200000000 # maximum XID age before forced vacuum # (change requires restart) #autovacuum_vacuum_cost_delay = -1 # default vacuum cost delay for # autovacuum, -1 means use # vacuum_cost_delay #autovacuum_vacuum_cost_limit = -1 # default vacuum cost limit for # autovacuum, -1 means use # vacuum_cost_limit #--------------------------------------------------------------------------- # CLIENT CONNECTION DEFAULTS #--------------------------------------------------------------------------- # - Statement Behavior - #search_path = '"$user",public' # schema names #default_tablespace = '' # a tablespace name, '' uses # the default #check_function_bodies = on #default_transaction_isolation = 'read committed' #default_transaction_read_only = off #statement_timeout = 0 # 0 is disabled #vacuum_freeze_min_age = 100000000 # - Locale and Formatting - datestyle = 'iso, mdy' #timezone = unknown # actually, defaults to TZ # environment setting #timezone_abbreviations = 'Default' # select the set of available timezone # abbreviations. Currently, there are # Default # Australia # India # However you can also create your own # file in share/timezonesets/. #extra_float_digits = 0 # min -15, max 2 #client_encoding = sql_ascii # actually, defaults to database # encoding # These settings are initialized by initdb -- they might be changed lc_messages = 'C' # locale for system error message # strings lc_monetary = 'C' # locale for monetary formatting lc_numeric = 'C' # locale for number formatting lc_time = 'C' # locale for time formatting # - Other Defaults - #explain_pretty_print = on #dynamic_library_path = '$libdir' #local_preload_libraries = '' #--------------------------------------------------------------------------- # LOCK MANAGEMENT #--------------------------------------------------------------------------- #deadlock_timeout = 1s #max_locks_per_transaction = 64 # min 10 # (change requires restart) # Note: each lock table slot uses ~270 bytes of shared memory, and there are # max_locks_per_transaction * (max_connections + max_prepared_transactions) # lock table slots. #--------------------------------------------------------------------------- # VERSION/PLATFORM COMPATIBILITY #--------------------------------------------------------------------------- # - Previous Postgres Versions - #add_missing_from = off #array_nulls = on #backslash_quote = safe_encoding # on, off, or safe_encoding #default_with_oids = off #escape_string_warning = on #standard_conforming_strings = off #regex_flavor = advanced # advanced, extended, or basic #sql_inheritance = on # - Other Platforms & Clients - #transform_null_equals = off #--------------------------------------------------------------------------- # CUSTOMIZED OPTIONS #--------------------------------------------------------------------------- #custom_variable_classes = '' # list of custom variable class names SELECT * FROM pg_stat_activity; datid | datname | procpid | usesysid | usename | current_query | waiting | query_start | backend_start | client_addr | client_port -------+---------+---------+----------+---------+---------------------------------+---------+-------------------------------+-------------------------------+-------------+------------- 16384 | hqdb | 3267 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.036781+01 | 2011-02-08 15:51:20.02413+01 | 127.0.0.1 | 47892 16384 | hqdb | 3268 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.050994+01 | 2011-02-08 15:51:20.047393+01 | 127.0.0.1 | 47893 16384 | hqdb | 3269 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.056661+01 | 2011-02-08 15:51:20.053201+01 | 127.0.0.1 | 47894 16384 | hqdb | 3271 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.062351+01 | 2011-02-08 15:51:20.058822+01 | 127.0.0.1 | 47895 16384 | hqdb | 3272 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.068328+01 | 2011-02-08 15:51:20.064517+01 | 127.0.0.1 | 47896 16384 | hqdb | 3273 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.07444+01 | 2011-02-08 15:51:20.070755+01 | 127.0.0.1 | 47897 16384 | hqdb | 3274 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.080941+01 | 2011-02-08 15:51:20.076983+01 | 127.0.0.1 | 47898 16384 | hqdb | 3275 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.08741+01 | 2011-02-08 15:51:20.083697+01 | 127.0.0.1 | 47899 16384 | hqdb | 3276 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.093597+01 | 2011-02-08 15:51:20.089977+01 | 127.0.0.1 | 47900 16384 | hqdb | 3277 | 10 | hqadmin | <IDLE> in transaction | f | 2011-02-08 15:51:20.133974+01 | 2011-02-08 15:51:20.096149+01 | 127.0.0.1 | 47901 16384 | hqdb | 3308 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:49:27.402197+01 | 2011-02-08 15:51:29.826321+01 | 127.0.0.1 | 47902 16384 | hqdb | 3309 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.572395+01 | 2011-02-08 15:51:29.865243+01 | 127.0.0.1 | 47903 16384 | hqdb | 3310 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.586273+01 | 2011-02-08 15:51:29.874346+01 | 127.0.0.1 | 47904 16384 | hqdb | 3311 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:10:03.024088+01 | 2011-02-08 15:51:29.883598+01 | 127.0.0.1 | 47905 16384 | hqdb | 3312 | 10 | hqadmin | <IDLE> in transaction | f | 2011-02-08 15:51:35.804457+01 | 2011-02-08 15:51:29.892925+01 | 127.0.0.1 | 47906 16384 | hqdb | 3418 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.580207+01 | 2011-02-08 15:51:55.56911+01 | 127.0.0.1 | 47910 16384 | hqdb | 3419 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.59781+01 | 2011-02-08 15:51:55.588609+01 | 127.0.0.1 | 47911 16384 | hqdb | 3422 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:10:02.668836+01 | 2011-02-08 15:51:55.603076+01 | 127.0.0.1 | 47914 16384 | hqdb | 3421 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.770427+01 | 2011-02-08 15:51:55.603086+01 | 127.0.0.1 | 47913 16384 | hqdb | 3420 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.680785+01 | 2011-02-08 15:51:55.637058+01 | 127.0.0.1 | 47912 16384 | hqdb | 18233 | 10 | hqadmin | SELECT * FROM pg_stat_activity; | f | 2011-02-09 10:49:29.688949+01 | 2011-02-09 10:48:13.031475+01 | | -1 (21 rows)

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• Explain why folder's permissions differ depending on HOW user is accessing server AFP vs SSH

  - by Meltemi

  Hoping someone can explain what is probably fairly obvious...but confuses me. Imagine two users with admin privileges on our server (Mac OS X Server 10.5). Call them joe & bob. both users are members of these groups: Staff Group ID: 20 Workgroup Group ID: 1025 Shared folder "devfolder" has sharing set as so: POSIX: Owner: joe read & write Group: admin read & write Other no access ACL: Workgroup Allow Read & write Question is why when looking at same folder does the ownership appear to change depending on who's doing the looking?!? Both looking at same folder on the server: From Joe's perspective: xserve:devfolder joe$ ls -l drwxrwxr-x 6 joe workgroup 204 May 20 19:32 app drwxrwxr-x 9 joe workgroup 306 May 20 19:32 config drwxrwxr-x 3 joe workgroup 102 May 20 19:32 db drwxrwxr-x 3 joe workgroup 102 May 20 19:32 doc drwxrwxr-x 3 joe workgroup 102 May 20 19:32 lib And from Bob's perspective (folder mounted on his machine via AFP): bobmac:devfolder bob$ ls -l drwxrwxr-x 6 bob _bob 264 May 20 19:32 app drwxrwxr-x 9 bob _bob 264 May 20 19:32 config drwxrwxr-x 3 bob _bob 264 May 20 19:32 db drwxrwxr-x 3 bob _bob 264 May 20 19:32 doc drwxrwxr-x 3 bob _bob 264 May 20 19:32 lib Now if Bob connects to server via SSH then his output is identical to Joe's, as expected. Can anyone tell me what the client is doing in this case and what should be expected when bob creates or updates files in this folder? What tools do I have to better understand this from the command line? Is this normal? Perhaps a "cleaner" way that wouldn't be confusing with "bob _bob"?!?

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• Windows XP only loads in VGA mode, and crashes when raising resolution

  - by Harel

  My kid's computer (Windows XP, SP3) started to (what appears to be) crash on boot. It will only boot in Safe or VGA mode, and if I try to raise the resolution from 640x480 it just reboots itself, and a error appears in the Event Log. When it loads up not in VGA mode, the monitor shuts off just after the windows logo is shown. It seems like windows is actually running but I can't see anything on screen (monitor is off for lack of signal). Nothing was installed recently that I know of, short of the usual windows updates. Thanks, Harel Below is the event log error: Event Type: Error Event Source: System Error Event Category: (102) Event ID: 1003 Date: 15/04/2012 Time: 16:27:11 User: N/A Computer: ----- Description: Error code 1000008e, parameter1 c0000005, parameter2 f745b0bf, parameter3 ede24f98, parameter4 00000000. For more information, see Help and Support Center at http://go.microsoft.com/fwlink/events.asp. Data: 0000: 53 79 73 74 65 6d 20 45 System E 0008: 72 72 6f 72 20 20 45 72 rror Er 0010: 72 6f 72 20 63 6f 64 65 ror code 0018: 20 31 30 30 30 30 30 38 1000008 0020: 65 20 20 50 61 72 61 6d e Param 0028: 65 74 65 72 73 20 63 30 eters c0 0030: 30 30 30 30 30 35 2c 20 000005, 0038: 66 37 34 35 62 30 62 66 f745b0bf 0040: 2c 20 65 64 65 32 34 66 , ede24f 0048: 39 38 2c 20 30 30 30 30 98, 0000 0050: 30 30 30 30 0000

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• How do I Geocode 20 addresses without receiving a OVER_QUERY_LIMIT response?

  - by michielvoo

  Using the Google Geocoder v3, if I try to geocode 20 addresses, I get a OVER_QUERY_LIMIT unless I time them to be ~1 second apart, but then it takes 20 seconds before the markers are all placed. Is there any other way to do it, other than storing the coordinates in advance?

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• LINQ und ArcObjects

  - by Marko Apfel

  LINQ und ArcObjects Motivation LINQ1 (language integrated query) ist eine Komponente des Microsoft .NET Frameworks seit der Version 3.5. Es erlaubt eine SQL-ähnliche Abfrage zu verschiedenen Datenquellen wie SQL, XML u.v.m. Wie SQL auch, bietet LINQ dazu eine deklarative Notation der Problemlösung - d.h. man muss nicht im Detail beschreiben wie eine Aufgabe, sondern was überhaupt zu lösen ist. Das befreit den Entwickler abfrageseitig von fehleranfälligen Iterator-Konstrukten. Ideal wäre es natürlich auf diese Möglichkeiten auch in der ArcObjects-Programmierung mit Features zugreifen zu können. Denkbar wäre dann folgendes Konstrukt: var largeFeatures = from feature in features where (feature.GetValue("SHAPE_Area").ToDouble() > 3000) select feature; bzw. dessen Äquivalent als Lambda-Expression: var largeFeatures = features.Where(feature => (feature.GetValue("SHAPE_Area").ToDouble() > 3000)); Dazu muss ein entsprechender Provider zu Verfügung stehen, der die entsprechende Iterator-Logik managt. Dies ist leichter als man auf den ersten Blick denkt - man muss nur die gewünschten Entitäten als IEnumerable<IFeature> liefern. (Anm.: nicht wundern - die Methoden GetValue() und ToDouble() habe ich nebenbei als Erweiterungsmethoden deklariert.) Im Hintergrund baut LINQ selbständig eine Zustandsmaschine (state machine)2 auf deren Ausführung verzögert ist (deferred execution)3 - d.h. dass erst beim tatsächlichen Anfordern von Entitäten (foreach, Count(), ToList(), ..) eine Instanziierung und Verarbeitung stattfindet, obwohl die Zuweisung schon an ganz anderer Stelle erfolgte. Insbesondere bei mehrfacher Iteration durch die Entitäten reibt man sich bei den ersten Debuggings verwundert die Augen wenn der Ausführungszeiger wie von Geisterhand wieder in die Iterator-Logik springt. Realisierung Eine ganz knappe Logik zum Konstruieren von IEnumerable<IFeature> lässt sich mittels Durchlaufen eines IFeatureCursor realisieren. Dazu werden die einzelnen Feature mit yield ausgegeben. Der einfachen Verwendung wegen, habe ich die Logik in eine Erweiterungsmethode GetFeatures() für IFeatureClass aufgenommen: public static IEnumerable GetFeatures(this IFeatureClass featureClass, IQueryFilter queryFilter, RecyclingPolicy policy) { IFeatureCursor featureCursor = featureClass.Search(queryFilter, RecyclingPolicy.Recycle == policy); IFeature feature; while (null != (feature = featureCursor.NextFeature())) { yield return feature; } //this is skipped in unit tests with cursor-mock if (Marshal.IsComObject(featureCursor)) { Marshal.ReleaseComObject(featureCursor); } } Damit kann man sich nun ganz einfach die IEnumerable<IFeature> erzeugen lassen: IEnumerable features = _featureClass.GetFeatures(RecyclingPolicy.DoNotRecycle); Etwas aufpassen muss man bei der Verwendung des "Recycling-Cursors". Nach einer verzögerten Ausführung darf im selben Kontext nicht erneut über die Features iteriert werden. In diesem Fall wird nämlich nur noch der Inhalt des letzten (recycelten) Features geliefert und alle Features sind innerhalb der Menge gleich. Kritisch würde daher das Konstrukt largeFeatures.ToList(). ForEach(feature => Debug.WriteLine(feature.OID)); weil ToList() schon einmal durch die Liste iteriert und der Cursor somit einmal durch die Features bewegt wurde. Die Erweiterungsmethode ForEach liefert dann immer dasselbe Feature. In derartigen Situationen darf also kein Cursor mit Recycling verwendet werden. Ein mehrfaches Ausführen von foreach ist hingegen kein Problem weil dafür jedes Mal die Zustandsmaschine neu instanziiert wird und somit der Cursor neu durchlaufen wird – das ist die oben schon erwähnte Magie. Ausblick Nun kann man auch einen Schritt weiter gehen und ganz eigene Implementierungen für die Schnittstelle IEnumerable<IFeature> in Angriff nehmen. Dazu müssen nur die Methode und das Property zum Zugriff auf den Enumerator ausprogrammiert werden. Im Enumerator selbst veranlasst man in der Reset()-Methode das erneute Ausführen der Suche – dazu übergibt man beispielsweise ein entsprechendes Delegate in den Konstruktur: new FeatureEnumerator( _featureClass, featureClass => featureClass.Search(_filter, isRecyclingCursor)); und ruft dieses beim Reset auf: public void Reset() {     _featureCursor = _resetCursor(_t); } Auf diese Art und Weise können Enumeratoren für völlig verschiedene Szenarien implementiert werden, die clientseitig restlos identisch nach obigen Schema verwendet werden. Damit verschmelzen Cursors, SelectionSets u.s.w. zu einer einzigen Materie und die Wiederverwendbarkeit von Code steigt immens. Obendrein lässt sich ein IEnumerable in automatisierten Unit-Tests sehr einfach mocken - ein großer Schritt in Richtung höherer Software-Qualität.4 Fazit Nichtsdestotrotz ist Vorsicht mit diesen Konstrukten in performance-relevante Abfragen geboten. Dadurch dass im Hintergrund eine Zustandsmaschine verwalten wird, entsteht einiges an Overhead dessen Verarbeitung zusätzliche Zeit kostet - ca. 20 bis 100 Prozent. Darüber hinaus ist auch das Arbeiten ohne Recycling schnell ein Performance-Gap. Allerdings ist deklarativer LINQ-Code viel eleganter, fehlerfreier und wartungsfreundlicher als das manuelle Iterieren, Vergleichen und Aufbauen einer Ergebnisliste. Der Code-Umfang verringert sich erfahrungsgemäß im Schnitt um 75 bis 90 Prozent! Dafür warte ich gerne ein paar Millisekunden länger. Wie so oft muss abgewogen werden zwischen Wartbarkeit und Performance - wobei für mich Wartbarkeit zunehmend an Priorität gewinnt. Zumeist ist sowieso nicht der Code sondern der Anwender die Bremse im Prozess. Demo-Quellcode support.esri.de   [1] Wikipedia: LINQ http://de.wikipedia.org/wiki/LINQ [2] Wikipedia: Zustandsmaschine http://de.wikipedia.org/wiki/Endlicher_Automat [3] Charlie Calverts Blog: LINQ and Deferred Execution http://blogs.msdn.com/b/charlie/archive/2007/12/09/deferred-execution.aspx [4] Clean Code Developer - gelber Grad/Automatisierte Unit Tests http://www.clean-code-developer.de/Gelber-Grad.ashx#Automatisierte_Unit_Tests_8

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• apache2.2 + php5 , process never die and stay blocked to LOCK_SH

  - by Givre

  Server version: Apache/2.2.22 (Unix) Server built: Mar 28 2012 16:31:45 Server's Module Magic Number: 20051115:30 Server loaded: APR 1.4.6, APR-Util 1.4.1 Compiled using: APR 1.4.6, APR-Util 1.4.1 Architecture: 64-bit Server MPM: Prefork threaded: no forked: yes (variable process count) Server compiled with.... -D APACHE_MPM_DIR="server/mpm/prefork" -D APR_HAS_SENDFILE -D APR_HAS_MMAP -D APR_HAVE_IPV6 (IPv4-mapped addresses enabled) -D APR_USE_SYSVSEM_SERIALIZE -D APR_USE_PTHREAD_SERIALIZE -D SINGLE_LISTEN_UNSERIALIZED_ACCEPT -D APR_HAS_OTHER_CHILD -D AP_HAVE_RELIABLE_PIPED_LOGS -D DYNAMIC_MODULE_LIMIT=128 -D HTTPD_ROOT="/opt/apache2" -D SUEXEC_BIN="/opt/apache2/bin/suexec" -D DEFAULT_PIDLOG="logs/httpd.pid" -D DEFAULT_SCOREBOARD="logs/apache_runtime_status" -D DEFAULT_LOCKFILE="logs/accept.lock" -D DEFAULT_ERRORLOG="logs/error_log" -D AP_TYPES_CONFIG_FILE="conf/mime.types" -D SERVER_CONFIG_FILE="conf/httpd.conf" Php5.2.17. Using mod_php5 as a DSO module compiled Problem: On shared webhosting, a lot of apache2 process never stop or die and they waiting as long as apache2 restart. Strace of one of theses process: access("tmp/meta_cache.txt", F_OK) = 0 getcwd("/home/exemple.com/htdocs"..., 4096) = 34 lstat("/var", {st_mode=S_IFDIR|0755, st_size=4096, ...}) = 0 lstat("/var/www", {st_mode=S_IFDIR|0755, st_size=4096, ...}) = 0 lstat("/home", {st_mode=S_IFDIR|0755, st_size=1715, ...}) = 0 lstat("/home/exemple.com", {st_mode=S_IFDIR|0755, st_size=16, ...}) = 0 lstat("/home/exemple.com/htdocs", {st_mode=S_IFDIR|0770, st_size=51, ...}) = 0 lstat("/home/exemple.com/htdocs/tmp", {st_mode=S_IFDIR|0777, st_size=51, ...}) = 0 lstat("/home/exemple.com/htdocs/tmp/meta_cache.txt", {st_mode=S_IFREG|0666, st_size=8901, ...}) = 0 lstat("/var", {st_mode=S_IFDIR|0755, st_size=4096, ...}) = 0 lstat("/var/www", {st_mode=S_IFDIR|0755, st_size=4096, ...}) = 0 lstat("/home", {st_mode=S_IFDIR|0755, st_size=1715, ...}) = 0 lstat("/home/exemple.com", {st_mode=S_IFDIR|0755, st_size=16, ...}) = 0 lstat("/home/exemple.com/htdocs", {st_mode=S_IFDIR|0770, st_size=51, ...}) = 0 lstat("/home/exemple.com/htdocs/tmp", {st_mode=S_IFDIR|0777, st_size=51, ...}) = 0 lstat("/home/exemple.com/htdocs/tmp/meta_cache.txt", {st_mode=S_IFREG|0666, st_size=8901, ...}) = 0 lstat("/var", {st_mode=S_IFDIR|0755, st_size=4096, ...}) = 0 lstat("/var/www", {st_mode=S_IFDIR|0755, st_size=4096, ...}) = 0 lstat("/home", {st_mode=S_IFDIR|0755, st_size=1715, ...}) = 0 lstat("/home/exemple.com", {st_mode=S_IFDIR|0755, st_size=16, ...}) = 0 getcwd("/home/exemple.com/htdocs"..., 4096) = 34 lstat("/var", {st_mode=S_IFDIR|0755, st_size=4096, ...}) = 0 lstat("/var/www", {st_mode=S_IFDIR|0755, st_size=4096, ...}) = 0 lstat("/home", {st_mode=S_IFDIR|0755, st_size=1715, ...}) = 0 lstat("/home/exemple.com", {st_mode=S_IFDIR|0755, st_size=16, ...}) = 0 lstat("/home/exemple.com/htdocs", {st_mode=S_IFDIR|0770, st_size=51, ...}) = 0 lstat("/home/exemple.com/htdocs/tmp", {st_mode=S_IFDIR|0777, st_size=51, ...}) = 0 lstat("/home/exemple.com/htdocs/tmp/meta_cache.txt", {st_mode=S_IFREG|0666, st_size=8901, ...}) = 0 open("/home/exemple.com/htdocs/tmp/meta_cache.txt", O_RDONLY) = 10905 fstat(10905, {st_mode=S_IFREG|0666, st_size=8901, ...}) = 0 lseek(10905, 0, SEEK_CUR) = 0 flock(10905, LOCK_SH) = The process never die, and stay like this. All files are on NFS V3 I'dont know how to solve this problem or find more informations. The effect is that all apache2 process become used and apache2 crash totaly . Thanks for you help.

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• Recommendations for a Hex Viewer Control for Windows.Forms?

  - by Fred F.

  I need ability to display content in Hex View, like this from WinHex Offset 0 1 2 3 4 5 6 7 8 9 A B C D E F 00000000 EF BB BF 0D 0A 4D 69 63 72 6F 73 6F 66 74 20 56 ..Microsoft V 00000010 69 73 75 61 6C 20 53 74 75 64 69 6F 20 53 6F 6C isual Studio Sol 00000020 75 74 69 6F 6E 20 46 69 6C 65 2C 20 46 6F 72 6D ution File, Form 00000030 61 74 20 56 65 72 73 69 6F 6E 20 31 30 2E 30 30 at Version 10.00 00000040 0D 0A 23 20 56 69 73 75 61 6C 20 53 74 75 64 69 ..# Visual Studi 00000050 6F 20 32 30 30 38 0D 0A 50 72 6F 6A 65 63 74 28 o 2008..Project( 00000060 22 7B 46 31 38 34 42 30 38 46 2D 43 38 31 43 2D "{F184B08F-C81C- 00000070 34 35 46 36 2D 41 35 37 46 2D 35 41 42 44 39 39 45F6-A57F-5ABD99 Please recommend a control. Thank you.

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• How to make 20 bit address by using two 16 bit registers?

  - by Zia ur Rahman

  IAPX88 can deal with 1 mega byte memory(20 bit addressing), now my question is how we make a 20 bit address by using two 16 bit registers.please give an example.

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• How can I possibly sort this in JavaScript?

  - by orokusaki

  I've been pounding my head on the wall trying to figure out how to sort this in JavaScript (I have to work with it in this format unfortunately). I need to sort it based on Small, Medium, Large, XL, XXL (Small ranking the highest) in each variationValues size field. The problem is that I need to sort the variationCosts and variationInventories at the same time to match the new order (since each value in order corresponds to the values in the other fields :( Input I have to work with var m = { variationNames: ["Length", "Size" ], variationValues: [ ["26.5\"", "XXL"], ["25\"", "Large"], ["25\"", "Medium"], ["25\"", "Small"], ["25\"", "XL"], ["25\"", "XXL"], ["26.5\"", "Large"], ["26.5\"", "Small"], ["26.5\"", "XL"] ], variationCosts: [ 20.00, 20.00, 20.00, 20.00, 20.00, 20.00, 20.00, 20.00, 20.00 ], variationInventories: [ 10, 60, 51, 10, 15, 10, 60, 10, 15 ], parentCost: 20.00 }; Desired output var m = { variationNames: ["Length", "Size" ], variationValues: [ ["25\"", "Small"], ["26.5\"", "Small"], ["25\"", "Medium"], ["25\"", "Large"], ["26.5\"", "Large"], ["25\"", "XL"], ["26.5\"", "XL"] ["25\"", "XXL"], ["26.5\"", "XXL"], ], variationCosts: [ 20.00, 20.00, 20.00, 20.00, 20.00, 20.00, 20.00, 20.00, 20.00 ], variationInventories: [ 10, 10, 51, 60, 15, 15, 15, 10, 10 ], parentCost: 20.00 };

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• i have a date (eg: 2010-04-17 ) i need the date of after 20 days from this date

  - by Ranjana

  i have a date (eg: 2010-04-17 ) i need the date of after 20 days from this date How to get the date after 20 days i.e next month some date. either in sql or in c#

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• why does Virtualbox use 15-20% CPU when VM is paused?

  - by laramichaels

  Hello, I run VirtualBox 3.1 on Ubuntu with a Win XP guest. I have noticed to my surprise that when I pause the VM (its screen grays out) VirtualBox continues using 15-20% of the host's CPU. Is this normal behavior? Is there a way to avoid it? (Without saving the state of the VM and exiting VirtualBox.) Thanks for any insights! ~lara

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• Postmaster uses excessive CPU and Disk Writes

  - by wolfcastle

  using PostgreSQL 9.1.2 I'm seeing excessive CPU usage and large amounts of writes to disk from postmaster tasks. This happens even while my application is doing almost nothing (10s of inserts per MINUTE). There are a reasonable number of connections open however. I've been trying to determine what in my application is causing this. I'm pretty newb with postgresql, and haven't gotten anywhere so far. I've turned on some logging options in my config file, and looked at connections in the pg_stat_activity table, but they are all idle. Yet each connection consumes ~ 50% CPU, and is writing ~15M/s to disk (reading nothing). I'm basically using the stock postgresql.conf with very little tweaks. I'd appreciate any advice or pointers on what I can do to track this down. Here is a sample of what top/iotop is showing me: Cpu(s): 18.9%us, 14.4%sy, 0.0%ni, 53.4%id, 11.8%wa, 0.0%hi, 1.5%si, 0.0%st Mem: 32865916k total, 7263720k used, 25602196k free, 575608k buffers Swap: 16777208k total, 0k used, 16777208k free, 4464212k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 17057 postgres 20 0 236m 33m 13m R 45.0 0.1 73:48.78 postmaster 17188 postgres 20 0 219m 15m 11m R 42.3 0.0 61:45.57 postmaster 17963 postgres 20 0 219m 16m 11m R 42.3 0.1 27:15.01 postmaster 17084 postgres 20 0 219m 15m 11m S 41.7 0.0 63:13.64 postmaster 17964 postgres 20 0 219m 17m 12m R 41.7 0.1 27:23.28 postmaster 18688 postgres 20 0 219m 15m 11m R 41.3 0.0 63:46.81 postmaster 17088 postgres 20 0 226m 24m 12m R 41.0 0.1 64:39.63 postmaster 24767 postgres 20 0 219m 17m 12m R 41.0 0.1 24:39.24 postmaster 18660 postgres 20 0 219m 14m 9.9m S 40.7 0.0 60:51.52 postmaster 18664 postgres 20 0 218m 15m 11m S 40.7 0.0 61:39.61 postmaster 17962 postgres 20 0 222m 19m 11m S 40.3 0.1 11:48.79 postmaster 18671 postgres 20 0 219m 14m 9m S 39.4 0.0 60:53.21 postmaster 26168 postgres 20 0 219m 15m 10m S 38.4 0.0 59:04.55 postmaster Total DISK READ: 0.00 B/s | Total DISK WRITE: 195.97 M/s TID PRIO USER DISK READ DISK WRITE SWAPIN IO> COMMAND 17962 be/4 postgres 0.00 B/s 14.83 M/s 0.00 % 0.25 % postgres: aggw aggw [local] idle 17084 be/4 postgres 0.00 B/s 15.53 M/s 0.00 % 0.24 % postgres: aggw aggw [local] idle 17963 be/4 postgres 0.00 B/s 15.00 M/s 0.00 % 0.24 % postgres: aggw aggw [local] idle 17188 be/4 postgres 0.00 B/s 14.80 M/s 0.00 % 0.24 % postgres: aggw aggw [local] idle 17964 be/4 postgres 0.00 B/s 15.50 M/s 0.00 % 0.24 % postgres: aggw aggw [local] idle 18664 be/4 postgres 0.00 B/s 15.13 M/s 0.00 % 0.23 % postgres: aggw aggw [local] idle 17088 be/4 postgres 0.00 B/s 14.71 M/s 0.00 % 0.13 % postgres: aggw aggw [local] idle 18688 be/4 postgres 0.00 B/s 14.72 M/s 0.00 % 0.00 % postgres: aggw aggw [local] idle 24767 be/4 postgres 0.00 B/s 14.93 M/s 0.00 % 0.00 % postgres: aggw aggw [local] idle 18671 be/4 postgres 0.00 B/s 16.14 M/s 0.00 % 0.00 % postgres: aggw aggw [local] idle 17057 be/4 postgres 0.00 B/s 13.58 M/s 0.00 % 0.00 % postgres: aggw aggw [local] idle 26168 be/4 postgres 0.00 B/s 15.50 M/s 0.00 % 0.00 % postgres: aggw aggw [local] idle 18660 be/4 postgres 0.00 B/s 15.85 M/s 0.00 % 0.00 % postgres: aggw aggw [local] idle

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• Webserver Responses Hanging

  - by drscroogemcduck

  From some networks requesting certain images on our webserver is very flakey. I've looked at tcpdumps on both sides and the server sends back part of the file and the client ACKs the TCP packet but the server never receives the ACK. The servers view: 41 19.941136 212.169.34.114 209.20.73.85 TCP 52456 > http [SYN] Seq=0 Win=8192 Len=0 MSS=1460 WS=2 42 19.941136 209.20.73.85 212.169.34.114 TCP http > 52456 [SYN, ACK] Seq=0 Ack=1 Win=5440 Len=0 MSS=1360 46 20.041142 212.169.34.114 209.20.73.85 TCP 52456 > http [ACK] Seq=1 Ack=1 Win=65280 Len=0 47 20.045142 212.169.34.114 209.20.73.85 HTTP GET /map/map/s+74-WBkWk0aR28Yy-YjXA== HTTP/1.1 48 20.045142 209.20.73.85 212.169.34.114 TCP http > 52456 [ACK] Seq=1 Ack=522 Win=6432 Len=0 49 20.045142 209.20.73.85 212.169.34.114 TCP [TCP segment of a reassembled PDU] (Part of the content of the image 2720 bytes. i assume it is reassembled in tcpdump and it is fragmented over the wire.) ** never receives the ACK sent in frame 282 and will eventually resend the tcp segment ** The clients view: 274 26.161773 10.0.16.67 209.20.73.85 TCP 52456 > http [SYN] Seq=0 Win=8192 Len=0 MSS=1460 WS=2 276 26.262867 209.20.73.85 10.0.16.67 TCP http > 52456 [SYN, ACK] Seq=0 Ack=1 Win=5440 Len=0 MSS=1360 277 26.263255 10.0.16.67 209.20.73.85 TCP 52456 > http [ACK] Seq=1 Ack=1 Win=65280 Len=0 278 26.265193 10.0.16.67 209.20.73.85 HTTP GET /map/map/s+74-WBkWk0aR28Yy-YjXA== HTTP/1.1 279 26.365562 209.20.73.85 10.0.16.67 TCP http > 52456 [ACK] Seq=1 Ack=522 Win=6432 Len=0 280 26.368002 209.20.73.85 10.0.16.67 TCP [TCP segment of a reassembled PDU] (Part of the content of the image. Only 1400 bytes.) 282 26.571380 10.0.16.67 209.20.73.85 TCP 52456 > http [ACK] Seq=522 Ack=1361 Win=65280 Len=0 The network we are having trouble with is NATd. Is there any kind of explanation for this weirdness?

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• How to type 10,20,30 etc using Photoshop "vertical type tool"?

  - by metal gear solid

  How to type 10,20,30 etc using Photoshop "vertical type tool"? I need like this 1 2 3 4 6 7 8 9 10 but in photoshop it's comes like this 1 2 3 4 6 7 8 9 1 0

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• Changing MS Project to 20-hour or 30-hour week.

  - by Eric

  I'm working on a project in MS Project and the default is a 40-hour week. I'm putting each individual task in based on a number of hours, not days. I'd like to have the whole thing set up and computing at 40-hour weeks, and then change it to 20 hours and have the project recompute. How do I do this? I think it has something to do with changing the "project calendar" but I can't quite figure it out.

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• Guten Rutsch und auf ein Neues!

  - by A&C Redaktion

  Wir hoffen, Sie haben erholsame Weihnachtstage im Familien- und Freundeskreis verbracht. Die ruhige Zeit vor Neujahr möchten wir nutzen, um einen Blick zurück auf das vergangene Jahr zu werfen - und dann vor allem nach vorne zu schauen.In erster Linie möchten wir uns ganz herzlich bei Ihnen bedanken. 40 Prozent des Umsatzes generieren die Oracle Partner auf der ganzen Welt, sie verantworten 80 Prozent unserer Transaktionen. Als Partner bilden Sie damit eine zentrale Säule im Gesamtgeschäft von Oracle. Deshalb kommt es uns darauf an, Ihnen alle Unterstützung zukommen zu lassen, die Sie brauchen. Unsere Spezialisierungsprogramme helfen Ihnen, Ihre Teams zielgerichtet und effizient zu qualifizieren. Im Blog finden Sie eine ganze Reihe von Beispielen für die vielfältige Unterstützung, die Oracle Ihnen bietet.Eröffnet haben wir den Blog im Oktober mit einem Live-Bericht vom OPN Day Satellite in Frankfurt. Seither sind regelmäßig interessante Beiträge dazugekommen. In den Videobeiträgen beispielsweise geben Oracle Experten und erfolgreiche Partner Einblicke in ihre Schwerpunktthemen. Sie können sich über die Säulen informieren, auf denen die Partnerstrategie von Oracle steht und über die Marketing-Programme, auf die Sie als Oracle Partner zurückgreifen können, wenn Sie Unterstützung brauchen.Aber wir wollen nicht nur informieren, sondern mit Ihnen in den Dialog treten. Der Partner-Blog will sich mit den Themen befassen, die Ihnen wichtig sind: Wo gibt es Verbesserungsbedarf? Wo läuft die Zusammenarbeit gut und vor allem: Warum? Was raten Sie anderen Partnern, die ins Partnerprogramm bei Oracle einsteigen möchten? Wie kann ich als ISV mehr Demand generieren?Auf all diese Fragen gibt es Antworten. Und dieser Blog ist die Plattform, auf der Fragen und Antworten zueinander finden. Als Oracle Partner sind Sie Teil dieser „Community". Machen Sie mit, wir freuen uns auf Ihre Beiträge! Senden Sie Ihre Themenvorschläge einfach direkt an [email protected] blicken zurück auf ein ereignisreiches Jahr. Als Partner haben Sie einen erheblichen Anteil daran, dass es auch ein erfolgreiches Jahr geworden ist. Dafür danken wir Ihnen herzlich. Wir freuen uns darauf, Sie auch im neuen Jahr hier im Blog zu begrüßen.Ihr A&C Redaktionsteam

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• AutoVue Integrates with Primavera P6

  - by celine.beck

  Oracle's Primavera P6 Enterprise Project Portfolio Management is an integrated project portfolio management (PPM) application that helps select the right strategic mix of projects, balance resource capacity, manage project risk and complete projects on time and within budget. AutoVue 19.3 and later versions (release 20.0) now integrate out of the box with the Web version of Oracle Primavera P6 release 7. The integration between the two products, which was announced during Oracle Open World 2009, provides project teams with ready access to any project documents directly from within the context of P6 in support for project scope definition and project planning and execution. You can learn more about the integration between AutoVue and Primavera P6 by: Listening to the Oracle Appcast entitled Enhance Primavera Project Document Collaboration with AutoVue Enterprise Visualization Watching an Oracle Webcast about how to improve project success with document visualization and collaboration Watching a recorded demo of the integrated solution Teams involved in complex projects like construction or plant shutdown activities are highly interdependent: the decisions of one affecting the actions of many others. This coupled with increasing project complexity, a vast array of players and heavy engineering and document-intensive workflows makes it more challenging to complete jobs on time and within budget. Organizations need complete visibility into project information, as well as robust project planning, risk analysis and resource balancing capabilities similar to those featured in Primavera P6 ; they also need to make sure that all project stakeholders, even those who neither understand engineering drawings nor are interested in engineering details that go beyond their specific needs, have ready access to technically advanced project information. This is exactly what the integration between AutoVue and Primavera delivers: ready access to any project information attached to Primavera projects, tasks or activities via AutoVue. There is no need for users to waste time searching for project-related documents or disrupting engineers for printouts, users have all the context they need to make sound decisions right from within Primavera P6 with a single click of a button. We are very excited about this new integration. If you are using Primavera and / or Primavera tied with AutoVue, we would be interested in getting your feedback on this integration! Please do not hesitate to post your comments / reactions on the blog!

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• Sorting Algorithms

  - by MarkPearl

  General Every time I go back to university I find myself wading through sorting algorithms and their implementation in C++. Up to now I haven’t really appreciated their true value. However as I discovered this last week with Dictionaries in C# – having a knowledge of some basic programming principles can greatly improve the performance of a system and make one think twice about how to tackle a problem. I’m going to cover briefly in this post the following: Selection Sort Insertion Sort Shellsort Quicksort Mergesort Heapsort (not complete) Selection Sort Array based selection sort is a simple approach to sorting an unsorted array. Simply put, it repeats two basic steps to achieve a sorted collection. It starts with a collection of data and repeatedly parses it, each time sorting out one element and reducing the size of the next iteration of parsed data by one. So the first iteration would go something like this… Go through the entire array of data and find the lowest value Place the value at the front of the array The second iteration would go something like this… Go through the array from position two (position one has already been sorted with the smallest value) and find the next lowest value in the array. Place the value at the second position in the array This process would be completed until the entire array had been sorted. A positive about selection sort is that it does not make many item movements. In fact, in a worst case scenario every items is only moved once. Selection sort is however a comparison intensive sort. If you had 10 items in a collection, just to parse the collection you would have 10+9+8+7+6+5+4+3+2=54 comparisons to sort regardless of how sorted the collection was to start with. If you think about it, if you applied selection sort to a collection already sorted, you would still perform relatively the same number of iterations as if it was not sorted at all. Many of the following algorithms try and reduce the number of comparisons if the list is already sorted – leaving one with a best case and worst case scenario for comparisons. Likewise different approaches have different levels of item movement. Depending on what is more expensive, one may give priority to one approach compared to another based on what is more expensive, a comparison or a item move. Insertion Sort Insertion sort tries to reduce the number of key comparisons it performs compared to selection sort by not “doing anything” if things are sorted. Assume you had an collection of numbers in the following order… 10 18 25 30 23 17 45 35 There are 8 elements in the list. If we were to start at the front of the list – 10 18 25 & 30 are already sorted. Element 5 (23) however is smaller than element 4 (30) and so needs to be repositioned. We do this by copying the value at element 5 to a temporary holder, and then begin shifting the elements before it up one. So… Element 5 would be copied to a temporary holder 10 18 25 30 23 17 45 35 – T 23 Element 4 would shift to Element 5 10 18 25 30 30 17 45 35 – T 23 Element 3 would shift to Element 4 10 18 25 25 30 17 45 35 – T 23 Element 2 (18) is smaller than the temporary holder so we put the temporary holder value into Element 3. 10 18 23 25 30 17 45 35 – T 23   We now have a sorted list up to element 6. And so we would repeat the same process by moving element 6 to a temporary value and then shifting everything up by one from element 2 to element 5. As you can see, one major setback for this technique is the shifting values up one – this is because up to now we have been considering the collection to be an array. If however the collection was a linked list, we would not need to shift values up, but merely remove the link from the unsorted value and “reinsert” it in a sorted position. Which would reduce the number of transactions performed on the collection. So.. Insertion sort seems to perform better than selection sort – however an implementation is slightly more complicated. This is typical with most sorting algorithms – generally, greater performance leads to greater complexity. Also, insertion sort performs better if a collection of data is already sorted. If for instance you were handed a sorted collection of size n, then only n number of comparisons would need to be performed to verify that it is sorted. It’s important to note that insertion sort (array based) performs a number item moves – every time an item is “out of place” several items before it get shifted up. Shellsort – Diminishing Increment Sort So up to now we have covered Selection Sort & Insertion Sort. Selection Sort makes many comparisons and insertion sort (with an array) has the potential of making many item movements. Shellsort is an approach that takes the normal insertion sort and tries to reduce the number of item movements. In Shellsort, elements in a collection are viewed as sub-collections of a particular size. Each sub-collection is sorted so that the elements that are far apart move closer to their final position. Suppose we had a collection of 15 elements… 10 20 15 45 36 48 7 60 18 50 2 19 43 30 55 First we may view the collection as 7 sub-collections and sort each sublist, lets say at intervals of 7 10 60 55 – 20 18 – 15 50 – 45 2 – 36 19 – 48 43 – 7 30 10 55 60 – 18 20 – 15 50 – 2 45 – 19 36 – 43 48 – 7 30 (Sorted) We then sort each sublist at a smaller inter – lets say 4 10 55 60 18 – 20 15 50 2 – 45 19 36 43 – 48 7 30 10 18 55 60 – 2 15 20 50 – 19 36 43 45 – 7 30 48 (Sorted) We then sort elements at a distance of 1 (i.e. we apply a normal insertion sort) 10 18 55 60 2 15 20 50 19 36 43 45 7 30 48 2 7 10 15 18 19 20 30 36 43 45 48 50 55 (Sorted) The important thing with shellsort is deciding on the increment sequence of each sub-collection. From what I can tell, there isn’t any definitive method and depending on the order of your elements, different increment sequences may perform better than others. There are however certain increment sequences that you may want to avoid. An even based increment sequence (e.g. 2 4 8 16 32 …) should typically be avoided because it does not allow for even elements to be compared with odd elements until the final sort phase – which in a way would negate many of the benefits of using sub-collections. The performance on the number of comparisons and item movements of Shellsort is hard to determine, however it is considered to be considerably better than the normal insertion sort. Quicksort Quicksort uses a divide and conquer approach to sort a collection of items. The collection is divided into two sub-collections – and the two sub-collections are sorted and combined into one list in such a way that the combined list is sorted. The algorithm is in general pseudo code below… Divide the collection into two sub-collections Quicksort the lower sub-collection Quicksort the upper sub-collection Combine the lower & upper sub-collection together As hinted at above, quicksort uses recursion in its implementation. The real trick with quicksort is to get the lower and upper sub-collections to be of equal size. The size of a sub-collection is determined by what value the pivot is. Once a pivot is determined, one would partition to sub-collections and then repeat the process on each sub collection until you reach the base case. With quicksort, the work is done when dividing the sub-collections into lower & upper collections. The actual combining of the lower & upper sub-collections at the end is relatively simple since every element in the lower sub-collection is smaller than the smallest element in the upper sub-collection. Mergesort With quicksort, the average-case complexity was O(nlog2n) however the worst case complexity was still O(N*N). Mergesort improves on quicksort by always having a complexity of O(nlog2n) regardless of the best or worst case. So how does it do this? Mergesort makes use of the divide and conquer approach to partition a collection into two sub-collections. It then sorts each sub-collection and combines the sorted sub-collections into one sorted collection. The general algorithm for mergesort is as follows… Divide the collection into two sub-collections Mergesort the first sub-collection Mergesort the second sub-collection Merge the first sub-collection and the second sub-collection As you can see.. it still pretty much looks like quicksort – so lets see where it differs… Firstly, mergesort differs from quicksort in how it partitions the sub-collections. Instead of having a pivot – merge sort partitions each sub-collection based on size so that the first and second sub-collection of relatively the same size. This dividing keeps getting repeated until the sub-collections are the size of a single element. If a sub-collection is one element in size – it is now sorted! So the trick is how do we put all these sub-collections together so that they maintain their sorted order. Sorted sub-collections are merged into a sorted collection by comparing the elements of the sub-collection and then adjusting the sorted collection. Lets have a look at a few examples… Assume 2 sub-collections with 1 element each 10 & 20 Compare the first element of the first sub-collection with the first element of the second sub-collection. Take the smallest of the two and place it as the first element in the sorted collection. In this scenario 10 is smaller than 20 so 10 is taken from sub-collection 1 leaving that sub-collection empty, which means by default the next smallest element is in sub-collection 2 (20). So the sorted collection would be 10 20 Lets assume 2 sub-collections with 2 elements each 10 20 & 15 19 So… again we would Compare 10 with 15 – 10 is the winner so we add it to our sorted collection (10) leaving us with 20 & 15 19 Compare 20 with 15 – 15 is the winner so we add it to our sorted collection (10 15) leaving us with 20 & 19 Compare 20 with 19 – 19 is the winner so we add it to our sorted collection (10 15 19) leaving us with 20 & _ 20 is by default the winner so our sorted collection is 10 15 19 20. Make sense? Heapsort (still needs to be completed) So by now I am tired of sorting algorithms and trying to remember why they were so important. I think every year I go through this stuff I wonder to myself why are we made to learn about selection sort and insertion sort if they are so bad – why didn’t we just skip to Mergesort & Quicksort. I guess the only explanation I have for this is that sometimes you learn things so that you can implement them in future – and other times you learn things so that you know it isn’t the best way of implementing things and that you don’t need to implement it in future. Anyhow… luckily this is going to be the last one of my sorts for today. The first step in heapsort is to convert a collection of data into a heap. After the data is converted into a heap, sorting begins… So what is the definition of a heap? If we have to convert a collection of data into a heap, how do we know when it is a heap and when it is not? The definition of a heap is as follows: A heap is a list in which each element contains a key, such that the key in the element at position k in the list is at least as large as the key in the element at position 2k +1 (if it exists) and 2k + 2 (if it exists). Does that make sense? At first glance I’m thinking what the heck??? But then after re-reading my notes I see that we are doing something different – up to now we have really looked at data as an array or sequential collection of data that we need to sort – a heap represents data in a slightly different way – although the data is stored in a sequential collection, for a sequential collection of data to be in a valid heap – it is “semi sorted”. Let me try and explain a bit further with an example… Example 1 of Potential Heap Data Assume we had a collection of numbers as follows 1[1] 2[2] 3[3] 4[4] 5[5] 6[6] For this to be a valid heap element with value of 1 at position [1] needs to be greater or equal to the element at position [3] (2k +1) and position [4] (2k +2). So in the above example, the collection of numbers is not in a valid heap. Example 2 of Potential Heap Data Lets look at another collection of numbers as follows 6[1] 5[2] 4[3] 3[4] 2[5] 1[6] Is this a valid heap? Well… element with the value 6 at position 1 must be greater or equal to the element at position [3] and position [4]. Is 6 > 4 and 6 > 3? Yes it is. Lets look at element 5 as position 2. It must be greater than the values at [4] & [5]. Is 5 > 3 and 5 > 2? Yes it is. If you continued to examine this second collection of data you would find that it is in a valid heap based on the definition of a heap.

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• BizTalk and IBM WebSphere MQ Errors

  - by Christopher House

  The project I'm currently working on is going to make heavy use of IBM WebShere MQ to send messages from BizTalk to the client's iSeries box.  I'd never previously worked with WebSphere MQ, so I didn't really have any idea what it would take to get this to work.  I was pleasantly surprised that it wasn't too difficult to configure a send port and pass messages through it to a queue.  Or so I thought... A couple of weeks ago, the client gave me the name of a host, queue manager and queue that I'd been using for my development.  Everything was going great, I was able to put messages onto the queue, I was happy, the client was happy.  Life was good.  Then the client tells me that the host I've been connecting to is actually a Solaris box and that in prod, we'll actually be sending to an iSeries.  We both agree that it would behoove us to start pointing my dev environment to their dev iSeries box in order to flush out any weirdness there might be.  As it turns out, it was a good thing we made the change.  As soon as I reconfigured my BRE policy that sets endpoint information to point to the iSeries queue, we started seeing failures in the event log.  An example from the event log: Event Type: Error Event Source: BizTalk Server 2009 Event Category: BizTalk Server 2009 Event ID: 5754 Date:  6/9/2010 Time:  10:16:41 AM User:  N/A Computer: WINDOWS2003 Description: A message sent to adapter "MQSC" on send port "<my dynamic sendport name>" with URI "mqsc://client/tcp/<hostname>(1414)/<queue manager name>/<queue name>" is suspended.  Error details: Failure encountered while attempting to open queue. queue = <queue name> queueManager = <queue manager name>, reasonCode = 6124  MessageId:  {76825C7C-611A-4A56-8A6F-35E1124BDB5C}  InstanceID: {BA389103-DF9B-493F-8C61-44574822AAD6} The key piece of information in the event entry is the reasonCode, 6124.  A quick Google search shows that reasonCode 6124 is the code for MQRC_NOT_CONNECTED.  According to IBM's docs, this means that you've tried to send a message without first opening a connection to the queue manager.  Obviously, in the context of BizTalk, this is an unexpected error, since this sort of thing should be managed entirely by the send adapter. Perusing IBM's documentation a bit more, I came across some info on how to turn on tracing for MQ.  With tracing enabled, I tried sending a message again, then went and reviewed the trace files.  The bulk of the information in the trace files didn't mean a thing to me, but at the end of one of the files, I did notice this: 00006257 15:40:20.327795   3500.4      RSESS:000009 ------{  reqReleaseConn 00006258 15:40:20.328714   3500.4      RSESS:000009 ------}  reqReleaseConn (rc=OK) 00006259 15:40:20.328727   3500.4      RSESS:000009 ------{  xcsClearTraceIdent 0000625A 15:40:20.328739   3500.4           :       ------}  xcsClearTraceIdent (rc=OK) 0000625B 15:40:20.328752   3500.4           :       -----}! trmzstMQCONNX (rc=MQRC_NOT_AUTHORIZED) 0000625C 15:40:20.328765   3500.4           :       ----}! MQCONNX (rc=MQRC_NOT_AUTHORIZED) 0000625D 15:40:20.328766   3500.4           :       ---}! ImqQueueManager::connect (rc=MQRC_NOT_AUTHORIZED) 0000625E 15:40:20.328767   3500.4           :       --}! ImqObject::open (rc=MQRC_NOT_CONNECTED) 0000625F 15:40:20.328768   3500.4           :       --{  ImqQueue::lock 00006260 15:40:20.328769   3500.4           :       --}! ImqQueue::lock (rc=Unknown(1)) 00006261 15:40:20.328769   3500.4           :       --{  ImqQueue::unlock 00006262 15:40:20.328769   3500.4           :       --}! ImqQueue::unlock (rc=Unknown(1)) It seemed like the MQRC_NOT_CONNECTED error was being caused by a security related issue (MQRC_NOT_AUTHORIZED).  I did notice something earlier in the log where it appeared that MQ was passing a field named UID with a value equal to the account name that my BizTalk service was running under.  I ended up creating a new local account on the BizTalk server that had the same name as a user which had access to the queue manager on the iSeries.  I then created a new host instance that ran under this new account, created a send handler for the MQSC adapter on this new host instance and reconfigured my orchestration to run on the new host instance.  After bouncing all my host instances, I was now able to send messages to the iSeries. It's still not clear to me why we were able to connect to the Solaris server.  I ended up contacting IBM's support and they did confirm that the process sending to MQ does in fact pass the identity to the queue manager it's connecting to.

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• SQL SERVER – Puzzle – Statistics are not Updated but are Created Once

  - by pinaldave

  After having excellent response to my quiz – Why SELECT * throws an error but SELECT COUNT(*) does not?I have decided to ask another puzzling question to all of you. I am running this test on SQL Server 2008 R2. Here is the quick scenario about my setup. Create Table Insert 1000 Records Check the Statistics Now insert 10 times more 10,000 indexes Check the Statistics – it will be NOT updated Note: Auto Update Statistics and Auto Create Statistics for database is TRUE Expected Result – Statistics should be updated – SQL SERVER – When are Statistics Updated – What triggers Statistics to Update Now the question is why the statistics are not updated? The common answer is – we can update the statistics ourselves using UPDATE STATISTICS TableName WITH FULLSCAN, ALL However, the solution I am looking is where statistics should be updated automatically based on algorithm mentioned here. Now the solution is to ____________________. Vinod Kumar is not allowed to take participate over here as he is the one who has helped me to build this puzzle. I will publish the solution on next week. Please leave a comment and if your comment consist valid answer, I will publish with due credit. Here is the script to reproduce the scenario which I mentioned. -- Execution Plans Difference -- Create Sample Database CREATE DATABASE SampleDB GO USE SampleDB GO -- Create Table CREATE TABLE ExecTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Insert One Thousand Records -- INSERT 1 INSERT INTO ExecTable (ID,FirstName,LastName,City) SELECT TOP 1000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%20 = 1 THEN 'New York' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 5 THEN 'San Marino' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 3 THEN 'Los Angeles' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 7 THEN 'La Cinega' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 13 THEN 'San Diego' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 17 THEN 'Las Vegas' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Display statistics of the table - none listed sp_helpstats N'ExecTable', 'ALL' GO -- Select Statement SELECT FirstName, LastName, City FROM ExecTable WHERE City  = 'New York' GO -- Display statistics of the table sp_helpstats N'ExecTable', 'ALL' GO -- Replace your Statistics over here -- NOTE: Replace your _WA_Sys with stats from above query DBCC SHOW_STATISTICS('ExecTable', _WA_Sys_00000004_7D78A4E7); GO -------------------------------------------------------------- -- Round 2 -- Insert Ten Thousand Records -- INSERT 2 INSERT INTO ExecTable (ID,FirstName,LastName,City) SELECT TOP 10000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%20 = 1 THEN 'New York' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 5 THEN 'San Marino' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 3 THEN 'Los Angeles' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 7 THEN 'La Cinega' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 13 THEN 'San Diego' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 17 THEN 'Las Vegas' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Select Statement SELECT FirstName, LastName, City FROM ExecTable WHERE City  = 'New York' GO -- Display statistics of the table sp_helpstats N'ExecTable', 'ALL' GO -- Replace your Statistics over here -- NOTE: Replace your _WA_Sys with stats from above query DBCC SHOW_STATISTICS('ExecTable', _WA_Sys_00000004_7D78A4E7); GO -- You will notice that Statistics are still updated with 1000 rows -- Clean up Database DROP TABLE ExecTable GO USE MASTER GO ALTER DATABASE SampleDB SET SINGLE_USER WITH ROLLBACK IMMEDIATE; GO DROP DATABASE SampleDB GO Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Statistics, Statistics

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• die $template->error() produces no line number

  - by Kinopiko

  In the following short program: use Template; my $template = Template->new (INCLUDE_PATH => "."); $template->process ("non-existent-file") or die $template->error (); why does "die" not produce a line number and newline? Output looks like this: $ perl template.pl file error - non-existent-file: not found ~ 503 $

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• Eine komplette Virtualisierungslandschaft auf dem eigenen Laptop – So geht’s

  - by Manuel Hossfeld

  Eine komplette Virtualisierungslandschaftauf dem eigenen Laptop – So geht’s Wenn man sich mit dem Virtualisierungsprodukt Oracle VM in der aktuellen Version 3.x näher befassen möchte, bietet es sich natürlich an, eine eigene Umgebung zu Lern- und Testzwecken zu installieren. Doch leichter gesagt als getan: Bei näherer Betrachtung der Architektur wird man schnell feststellen, dass mehrere Rechner benötigt werden, um überhaupt alle Komponenten abbilden zu können: Zum einen gilt es, den oder die OVM Server selbst zu installieren. Das ist recht leicht und schnell erledigt, aber da Oracle VM ein „Typ 1 Hypervisor ist“ - also direkt auf dem Rechner („bare metal“) installiert wird – ist der eigenen Arbeits-PC oder Laptop dafür recht ungeeignet. (Eine Dual-Boot Umgebung wäre zwar denkbar, aber recht unpraktisch.) Zum anderen wird auch ein Rechner benötigt, auf dem der OVM Manager installiert wird. Im Gegensatz zum OVM Server erfolgt dessen Installation nicht „bare metal“, sondern auf einem bestehenden Oracle Linux. Aber was tun, wenn man gerade keinen Linux-Server griffbereit hat und auch keine extra Hardware dafür opfern will? Möchte man alle Funktionen von Oracle VM austesten, so sollte man zusätzlich über einen Shared Storag everüfugen. Dieser kann wahlweise über NFS oder über ein SAN (per iSCSI oder FibreChannel) angebunden werden. Zwar braucht man zum Testen nicht zwingend entsprechende „echte“ Storage-Hardware, aber auch die „Simulation“ entsprechender Komponenten erfordert zusätzliche Hardware mit entsprechendem freien Plattenplatz.(Alternativ können auch fertige „Software Storage Appliances“ wie z.B. OpenFiler oder FreeNAS verwendet werden). Angenommen, es stehen tatsächlich keine „echte“ Server- und Storage Hardware zur Verfügung, so benötigt man für die oben genannten drei Punkte  drei bzw. vier Rechner (PCs, Laptops...) - je nachdem ob man einen oder zwei OVM Server starten möchte. Erfreulicherweise geht es aber auch mit deutlich weniger Aufwand: Wie bereits kurz im Blogpost anlässlich des letzten OVM-Releases 3.1.1 beschrieben, ist die aktuelle Version in der Lage, selbst vollständig innerhalb von VirtualBox als Gast zu laufen. Wer bei dieser „doppelten Virtualisierung“ nun an das Prinzip der russischen Matroschka-Puppen denkt, liegt genau richtig. Oracle VM VirtualBox stellt dabei gewissermaßen die äußere Hülle dar – und da es sich bei VirtualBox im Gegensatz zu Oracle VM Server um einen „Typ 2 Hypervisor“ handelt, funktioniert dieser Ansatz auch auf einem „normalen“ Arbeits-PC bzw. Laptop, ohne dessen eigentliche Betriebsystem komplett zu überschreiben. Doch das beste dabei ist: Die Installation der jeweiligen VirtualBox VMs muss man nicht selber durchführen. Der OVM Manager als auch der OVM Server stehen bereits als vorgefertigte „VirtualBox Appliances“ im Oracle Technology Network zum Download zur Verfügung und müssen im Grunde nur noch importiert und konfiguriert werden. Das folgende Schaubild verdeutlicht das Prinzip: Die dunkelgrünen Bereiche stellen jeweils Instanzen der eben erwähnten VirtualBox Appliances für OVM Server und OVM Manager dar. (Hier im Bild sind zwei OVM Server zu sehen, als Minimum würde natürlich auch einer genügen. Dann können aber viele Features wie z.B. OVM HA nicht ausprobieren werden.) Als cleveren Trick zur Einsparung einer weiteren VM für Storage-Zwecke hat Wim Coekaerts (Senior Vice President of Linux and Virtualization Engineering bei Oracle), der „Erbauer“ der VirtualBox Appliances, die OVM Manager Appliance bereits so vorbereitet, dass diese gleichzeitig als NFS-Share (oder ggf. sogar als iSCSI Target) dienen kann. Dies beschreibt er auch kurz auf seinem Blog. Die hellgrünen Ovale stellen die VMs dar, welche dann innerhalb einer der virtualisierten OVM Server laufen können. Aufgrund der Tatsache, dass durch diese „doppelte Virtualisierung“ die Fähigkeit zur Hardware-Virtualisierung verloren geht, können diese „Nutz-VMs“ demzufolge nur paravirtualisiert sein (PVM). Die hier in blau eingezeichneten Netzwerk-Schnittstellen sind virtuelle Interfaces, welche beliebig innerhalb von VirtualBox eingerichtet werden können. Wer die verschiedenen Netzwerk-Rollen innerhalb von Oracle VM im Detail ausprobieren will, kann hier natürlich auch mehr als zwei dieser Interfaces konfigurieren. Die Vorteile dieser Lösung für Test- und Demozwecke liegen auf der Hand: Mit lediglich einem PC bzw. Laptop auf dem VirtualBox installiert ist, können alle oben genannten Komponenten installiert und genutzt werden – genügend RAM vorausgesetzt. Als Minimum darf hier 8GB gelten. Soll auf der „Host-Umgebung“ (also dem PC auf dem VirtualBox läuft) nebenbei noch gearbeiten werden und/oder mehrere „Nutz-VMs“ in dieser simulierten OVM-Server-Umgebung laufen, empfehlen sich natürlich eher 16GB oder mehr. Da die nötigen Schritte zum Installieren und initialen Konfigurieren der Umgebung ausführlich in einem entsprechenden Paper beschrieben sind, möchte ich im Rest dieses Artikels noch einige zusätzliche Tipps und Details erwähnen, welche einem das Leben etwas leichter machen können: Um möglichst entstpannt und mit zusätzlichen „Sicherheitsnetz“ an die Konfiguration der Umgebung herangehen zu können, empfiehlt es sich, ausgiebigen Gebrauch von der in VirtualBox eingebauten Funktionalität der VM Snapshots zu machen. Dies ermöglicht nicht nur ein Zurücksetzen falls einmal etwas schiefgehen sollte, sondern auch ein beliebiges Wiederholen von bereits absolvierten Teilschritten (z.B. um eine andere Idee oder Variante der Umgebung auszuprobieren). Sowohl bei den gerade erwähnten Snapshots als auch bei den VMs selbst sollte man aussagekräftige Namen verwenden. So ist sichergestellt, dass man nicht durcheinander kommt und auch nach ein paar Wochen noch weiß, welche Umgebung man da eigentlich vor sich hat. Dies beinhaltet auch die genaue Versions- und Buildnr. des jeweiligen OVM-Releases. (Siehe dazu auch folgenden Screenshot.) Weitere Informationen und Details zum aktuellen Zustand sowie Zweck der jeweiligen VMs kann in dem oft übersehenen Beschreibungsfeld hinterlegt werden. Es empfiehlt sich, bereits VOR der Installation einen Notizzettel (oder eine Textdatei) mit den geplanten IP-Adressen und Namen für die VMs zu erstellen. (Nicht vergessen: Auch der Server Pool benötigt eine eigene IP.) Dabei sollte man auch nochmal die tatsächlichen Netzwerke der zu verwendenden Virtualbox-Interfaces prüfen und notieren. Achtung: Es gibt im Rahmen der Installation einige Passworte, die vom Nutzer gesetzt werden können – und solche, die zunächst fest eingestellt sind. Zu letzterem gehört das Passwort für den ovs-agent sowie den root-User auf den OVM Servern, welche beide per Default „ovsroot“ lauten. (Alle weiteren Passwort-Informationen sind in dem „Read me first“ Dokument zu finden, welches auf dem Desktop der OVM Manager VM liegt.) Aufpassen muss man ggf. auch in der initialen „Interview-Phase“ welche die VirtualBox VMs durchlaufen, nachdem sie das erste mal gebootet werden. Zu diesem Zeitpunkt ist nämlich auf jeden Fall noch die amerikanische Tastaturbelegung aktiv, so dass man z.B. besser kein „y“ und „z“ in seinem selbst gewählten Passwort verwendet. Aufgrund der Tatsache, dass wie oben erwähnt der OVM Manager auch gleichzeitig den Shared Storage bereitstellt, sollte darauf geachtet werden, dass dessen VM vor den OVM Server VMs gestartet wird. (Andernfalls „findet“ der dem OVM Server Pool zugrundeliegende Cluster sein sog. „Server Pool File System“ nicht.)

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