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  • Big Data – Buzz Words: What is HDFS – Day 8 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is MapReduce. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – HDFS. What is HDFS ? HDFS stands for Hadoop Distributed File System and it is a primary storage system used by Hadoop. It provides high performance access to data across Hadoop clusters. It is usually deployed on low-cost commodity hardware. In commodity hardware deployment server failures are very common. Due to the same reason HDFS is built to have high fault tolerance. The data transfer rate between compute nodes in HDFS is very high, which leads to reduced risk of failure. HDFS creates smaller pieces of the big data and distributes it on different nodes. It also copies each smaller piece to multiple times on different nodes. Hence when any node with the data crashes the system is automatically able to use the data from a different node and continue the process. This is the key feature of the HDFS system. Architecture of HDFS The architecture of the HDFS is master/slave architecture. An HDFS cluster always consists of single NameNode. This single NameNode is a master server and it manages the file system as well regulates access to various files. In additional to NameNode there are multiple DataNodes. There is always one DataNode for each data server. In HDFS a big file is split into one or more blocks and those blocks are stored in a set of DataNodes. The primary task of the NameNode is to open, close or rename files and directory and regulate access to the file system, whereas the primary task of the DataNode is read and write to the file systems. DataNode is also responsible for the creation, deletion or replication of the data based on the instruction from NameNode. In reality, NameNode and DataNode are software designed to run on commodity machine build in Java language. Visual Representation of HDFS Architecture Let us understand how HDFS works with the help of the diagram. Client APP or HDFS Client connects to NameSpace as well as DataNode. Client App access to the DataNode is regulated by NameSpace Node. NameSpace Node allows Client App to connect to the DataNode based by allowing the connection to the DataNode directly. A big data file is divided into multiple data blocks (let us assume that those data chunks are A,B,C and D. Client App will later on write data blocks directly to the DataNode. Client App does not have to directly write to all the node. It just has to write to any one of the node and NameNode will decide on which other DataNode it will have to replicate the data. In our example Client App directly writes to DataNode 1 and detained 3. However, data chunks are automatically replicated to other nodes. All the information like in which DataNode which data block is placed is written back to NameNode. High Availability During Disaster Now as multiple DataNode have same data blocks in the case of any DataNode which faces the disaster, the entire process will continue as other DataNode will assume the role to serve the specific data block which was on the failed node. This system provides very high tolerance to disaster and provides high availability. If you notice there is only single NameNode in our architecture. If that node fails our entire Hadoop Application will stop performing as it is a single node where we store all the metadata. As this node is very critical, it is usually replicated on another clustered as well as on another data rack. Though, that replicated node is not operational in architecture, it has all the necessary data to perform the task of the NameNode in the case of the NameNode fails. The entire Hadoop architecture is built to function smoothly even there are node failures or hardware malfunction. It is built on the simple concept that data is so big it is impossible to have come up with a single piece of the hardware which can manage it properly. We need lots of commodity (cheap) hardware to manage our big data and hardware failure is part of the commodity servers. To reduce the impact of hardware failure Hadoop architecture is built to overcome the limitation of the non-functioning hardware. Tomorrow In tomorrow’s blog post we will discuss the importance of the relational database in Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – ?Finding Out What Changed in a Deleted Database – Notes from the Field #041

    - by Pinal Dave
    [Note from Pinal]: This is a 41th episode of Notes from the Field series. The real world is full of challenges. When we are reading theory or book, we sometimes do not realize how real world reacts works and that is why we have the series notes from the field, which is extremely popular with developers and DBA. Let us talk about interesting problem of how to figure out what has changed in the DELETED database. Well, you think I am just throwing the words but in reality this kind of problems are making our DBA’s life interesting and in this blog post we have amazing story from Brian Kelley about the same subject. In this episode of the Notes from the Field series database expert Brian Kelley explains a how to find out what has changed in deleted database. Read the experience of Brian in his own words. Sometimes, one of the hardest questions to answer is, “What changed?” A similar question is, “Did anything change other than what we expected to change?” The First Place to Check – Schema Changes History Report: Pinal has recently written on the Schema Changes History report and its requirement for the Default Trace to be enabled. This is always the first place I look when I am trying to answer these questions. There are a couple of obvious limitations with the Schema Changes History report. First, while it reports what changed, when it changed, and who changed it, other than the base DDL operation (CREATE, ALTER, DELETE), it does not present what the changes actually were. This is not something covered by the default trace. Second, the default trace has a fixed size. When it hits that size, the changes begin to overwrite. As a result, if you wait too long, especially on a busy database server, you may find your changes rolled off. But the Database Has Been Deleted! Pinal cited another issue, and that’s the inability to run the Schema Changes History report if the database has been dropped. Thankfully, all is not lost. One thing to remember is that the Schema Changes History report is ultimately driven by the Default Trace. As you may have guess, it’s a trace, like any other database trace. And the Default Trace does write to disk. The trace files are written to the defined LOG directory for that SQL Server instance and have a prefix of log_: Therefore, you can read the trace files like any other. Tip: Copy the files to a working directory. Otherwise, you may occasionally receive a file in use error. With the Default Trace files, if you ask the question early enough, you can see the information for a deleted database just the same as any other database. Testing with a Deleted Database: Here’s a short script that will create a database, create a schema, create an object, and then drop the database. Without the database, you can’t do a standard Schema Changes History report. CREATE DATABASE DeleteMe; GO USE DeleteMe; GO CREATE SCHEMA Test AUTHORIZATION dbo; GO CREATE TABLE Test.Foo (FooID INT); GO USE MASTER; GO DROP DATABASE DeleteMe; GO This sets up the perfect situation where we can’t retrieve the information using the Schema Changes History report but where it’s still available. Finding the Information: I’ve sorted the columns so I can see the Event Subclass, the Start Time, the Database Name, the Object Name, and the Object Type at the front, but otherwise, I’m just looking at the trace files using SQL Profiler. As you can see, the information is definitely there: Therefore, even in the case of a dropped/deleted database, you can still determine who did what and when. You can even determine who dropped the database (loginame is captured). The key is to get the default trace files in a timely manner in order to extract the information. If you want to get started with performance tuning and database security with the help of experts, read more over at Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Security, SQL Server, SQL Tips and Tricks, T SQL

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  • Use your own domain email and tired of SPAM? SPAMfighter FTW

    - by Dave Campbell
    I wouldn't post this if I hadn't tried it... and I paid for it myself, so don't anybody be thinking I'm reviewing something someone sent me! Long ago and far away I got very tired of local ISPs and 2nd phone lines and took the plunge and got hooked up to cable... yeah I know the 2nd phone line concept may be hard for everyone to understand, but that's how it was in 'the old days'. To avoid having to change email addresses all the time, I decided to buy a domain name, get minimal hosting, and use that for all email into the house. That way if I changed providers, all the email addresses wouldn't have to change. Of course, about a dozen domains later, I have LOTS of pop email addresses and even an exchange address to my client's server... times have changed. What also has changed is the fact that we get SPAM... 'back in the day' when I was a beta tester for the first ISP in Phoenix, someone tried sending an ad to all of us, and what he got in return for his trouble was a bunch of core dumps that locked up his email... if you don't know what a core dump is, ask your grandfather. But in today's world, we're all much more civilized than that, and as with many things, the criminals seem to have much more rights than we do, so we get inundated with email offering all sorts of wild schemes that you'd have to be brain-dead to accept, but yet... if people weren't accepting them, they'd stop sending them. I keep hoping that survival of the smartest would weed out the mental midgets that respond and then the jumk email stop, but that hasn't happened yet anymore than finding high-quality hearing aids at the checkout line of Safeway because of all the dimwits playing music too loud inside their car... but that's another whole topic and I digress. So what's the solution for all the spam? And I mean *all*... on that old personal email address, I am now getting over 150 spam messages a day! Yes I know that's why God invented the delete key, but I took it on as a challenge, and it's a matter of principle... why should I switch email addresses, or convert from [email protected] to something else, or have all my email filtered through some service just because some A-Hole somewhere has a site up trying to phish Ma & Pa Kettle (ask your grandfather about that too) out of their retirement money? Well... I got an email from my cousin the other day while I was writing yet another email rule, and there was a banner on the bottom of his email that said he was protected by SPAMfighter. SPAMfighter huh.... so I took a look at their site, and found yet one more of the supposed tools to help us. But... I read that they're a Microsoft Gold Partner... and that doesn't come lightly... so I took a gamble and here's what I found: I installed it, and had to do a couple things: 1) SPAMfighter stuffed the SPAMfighter folder into my client's exchange address... I deleted it, made a new SPAMfighter folder where I wanted it to go, then in the SPAMfighter Clients settings for Outlook, I told it to put all spam there. 2) It didn't seem to be doing anything. There's a ribbon button that you can select "Block", and I did that, wondering if I was 'training' it, but it wasn't picking up duplicates 3) I sent email to support, and wrote a post on the forum (not to self: reply to that post). By the time the folks from the home office responded, it was the next day, and first up, SPAMfighter knocked down everything that came through when Outlook opend... two thumbs up! I disabled my 'garbage collection' rule from Outlook, and told Outlook not to use the junk folder thinking it was interfering. 4) Day 2 seemed to go about like Day 1... but I hung in there. 5) Day 3 is now a whole new day... I had left Outlook open and hadn't looked at the PC since sometime late yesterday afternoon, and when I looked this morning, *every bit* of spam was in the SPAMfighter folder!! I'm a new paying customer After watching SPAMfighter work this morning, I've purchased a 1-year license, and I now can sit and watch as emails come in and disappear from my inbox into the SPAMfighter folder. No more continual tweaking of the rules. I've got SPAMfighter set to 'Very Hard' filtering... personally I'd rather pull the few real emails out of the SPAMfighter folder than pull spam out of the real folders. Yes this is simply another way of using the delete key, but you know what? ... it feels good :) Here's a screenshot of the stats after just about 48 hours of being onboard: Note that all the ones blocked by me were during Day 1 and 2... I've blocked none today, and everything is blocked. Stay in the 'Light!

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  • SQL SERVER – Backing Up and Recovering the Tail End of a Transaction Log – Notes from the Field #042

    - by Pinal Dave
    [Notes from Pinal]: The biggest challenge which people face is not taking backup, but the biggest challenge is to restore a backup successfully. I have seen so many different examples where users have failed to restore their database because they made some mistake while they take backup and were not aware of the same. Tail Log backup was such an issue in earlier version of SQL Server but in the latest version of SQL Server, Microsoft team has fixed the confusion with additional information on the backup and restore screen itself. Now they have additional information, there are a few more people confused as they have no clue about this. Previously they did not find this as a issue and now they are finding tail log as a new learning. Linchpin People are database coaches and wellness experts for a data driven world. In this 42nd episode of the Notes from the Fields series database expert Tim Radney (partner at Linchpin People) explains in a very simple words, Backing Up and Recovering the Tail End of a Transaction Log. Many times when restoring a database over an existing database SQL Server will warn you about needing to make a tail end of the log backup. This might be your reminder that you have to choose to overwrite the database or could be your reminder that you are about to write over and lose any transactions since the last transaction log backup. You might be asking yourself “What is the tail end of the transaction log”. The tail end of the transaction log is simply any committed transactions that have occurred since the last transaction log backup. This is a very crucial part of a recovery strategy if you are lucky enough to be able to capture this part of the log. Most organizations have chosen to accept some amount of data loss. You might be shaking your head at this statement however if your organization is taking transaction logs backup every 15 minutes, then your potential risk of data loss is up to 15 minutes. Depending on the extent of the issue causing you to have to perform a restore, you may or may not have access to the transaction log (LDF) to be able to back up those vital transactions. For example, if the storage array or disk that holds your transaction log file becomes corrupt or damaged then you wouldn’t be able to recover the tail end of the log. If you do have access to the physical log file then you can still back up the tail end of the log. In 2013 I presented a session at the PASS Summit called “The Ultimate Tail Log Backup and Restore” and have been invited back this year to present it again. During this session I demonstrate how you can back up the tail end of the log even after the data file becomes corrupt. In my demonstration I set my database offline and then delete the data file (MDF). The database can’t become more corrupt than that. I attempt to bring the database back online to change the state to RECOVERY PENDING and then backup the tail end of the log. I can do this by specifying WITH NO_TRUNCATE. Using NO_TRUNCATE is equivalent to specifying both COPY_ONLY and CONTINUE_AFTER_ERROR. It as its name says, does not try to truncate the log. This is a great demo however how could I achieve backing up the tail end of the log if the failure destroys my entire instance of SQL and all I had was the LDF file? During my demonstration I also demonstrate that I can attach the log file to a database on another instance and then back up the tail end of the log. If I am performing proper backups then my most recent full, differential and log files should be on a server other than the one that crashed. I am able to achieve this task by creating new database with the same name as the failed database. I then set the database offline, delete my data file and overwrite the log with my good log file. I attempt to bring the database back online and then backup the log with NO_TRUNCATE just like in the first example. I encourage each of you to view my blog post and watch the video demonstration on how to perform these tasks. I really hope that none of you ever have to perform this in production, however it is a really good idea to know how to do this just in case. It really isn’t a matter of “IF” you will have to perform a restore of a production system but more of a “WHEN”. Being able to recover the tail end of the log in these sever cases could be the difference of having to notify all your business customers of data loss or not. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Note: Tim has also written an excellent book on SQL Backup and Recovery, a must have for everyone. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Centos CMake Does Not Install Using gcc 4.7.2

    - by Devin Dixon
    A similar problem has been reported here with no solution:https://www.centos.org/modules/newbb/print.php?form=1&topic_id=42696&forum=56&order=ASC&start=0 I've added and upgraded gcc to centos cd /etc/yum.repos.d wget http://people.centos.org/tru/devtools-1.1/devtools-1.1.repo yum --enablerepo=testing-1.1-devtools-6 install devtoolset-1.1-gcc devtoolset-1.1-gcc-c++ scl enable devtoolset-1.1 bash The result is this for my gcc [root@hhvm-build-centos cmake-2.8.11.1]# gcc -v Using built-in specs. COLLECT_GCC=gcc COLLECT_LTO_WRAPPER=/opt/centos/devtoolset-1.1/root/usr/libexec/gcc/x86_64-redhat-linux/4.7.2/lto-wrapper Target: x86_64-redhat-linux Configured with: ../configure --prefix=/opt/centos/devtoolset-1.1/root/usr --mandir=/opt/centos/devtoolset-1.1/root/usr/share/man --infodir=/opt/centos/devtoolset-1.1/root/usr/share/info --with-bugurl=http://bugzilla.redhat.com/bugzilla --enable-bootstrap --enable-shared --enable-threads=posix --enable-checking=release --disable-build-with-cxx --disable-build-poststage1-with-cxx --with-system-zlib --enable-__cxa_atexit --disable-libunwind-exceptions --enable-gnu-unique-object --enable-linker-build-id --enable-languages=c,c++,fortran,lto --enable-plugin --with-linker-hash-style=gnu --enable-initfini-array --disable-libgcj --with-ppl --with-cloog --with-mpc=/home/centos/rpm/BUILD/gcc-4.7.2-20121015/obj-x86_64-redhat-linux/mpc-install --with-tune=generic --with-arch_32=i686 --build=x86_64-redhat-linux Thread model: posix gcc version 4.7.2 20121015 (Red Hat 4.7.2-5) (GCC) And I tried to then install cmake through http://www.cmake.org/cmake/resources/software.html#latest But I keep running into this error: Linking CXX executable ../bin/ccmake /opt/centos/devtoolset-1.1/root/usr/libexec/gcc/x86_64-redhat-linux/4.7.2/ld: CMakeFiles/ccmake.dir/CursesDialog/cmCursesMainForm.cxx.o: undefined reference to symbol 'keypad' /opt/centos/devtoolset-1.1/root/usr/libexec/gcc/x86_64-redhat-linux/4.7.2/ld: note: 'keypad' is defined in DSO /lib64/libtinfo.so.5 so try adding it to the linker command line /lib64/libtinfo.so.5: could not read symbols: Invalid operation collect2: error: ld returned 1 exit status gmake[2]: *** [bin/ccmake] Error 1 gmake[1]: *** [Source/CMakeFiles/ccmake.dir/all] Error 2 gmake: *** [all] Error 2 The problem seems to come from the new gcc installed because it works with the default install. Is there a solution to this problem?

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  • How to get IIS7 to release a locked file?

    - by Jarrod Dixon
    During our production builds, a very large (10 megabyte) static content file in the root directory will sometimes be locked by IIS and cannot be deleted by the clean task. This is presumably because it is being actively served to one or more clients at the time. The build process stops the website before cleaning via c:\Windows\System32\inetsrv\appcmd.exe stop site http://oursite.com However, this does not release the file - we have to restart IIS to get the process to relinquish its lock. appcmd.exe allows you to take IIS down completely; we do not want to do this! Are there any other ways to get IIS to let go of a locked file, without restarting IIS? Simply stopping and starting the individual website is definitely not working to release the file lock.

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  • Cannot get git working

    - by Devin Dixon
    I'm trying to install my own git server with these instructions. http://cisight.com/how-to-setup-git-server-using-gitolite-in-ubuntu-11-10-oneiric/ But I am get stuck at this point. git clone --verbose [email protected]:testing.git Cloning into 'testing'... Permission denied (publickey). fatal: The remote end hung up unexpectedly And I think it has something to do with this: gitolite@ip-xxxx:~$ gl-setup tmp/john.pub key_read: uudecode Aklkdfgkldkgldkgldkgfdlkgldkgdlfkgldkgldkgdlkgkfdnknbkdnbkdnbkdnbkfnbkdfnbkdnfbkdfnbdknbkdnbkfnbkdbnkdbnkdfnbkd [email protected] failed fprint failed I always get the fail and I think its preventing me from cloning repo.The repo is there along with gitolite-admin.git repo. The permissions are this: drwxr-x--- 8 gitolite gitolite 4096 Jun 6 16:29 gitolite-admin.git drwxr-x--- 7 gitolite gitolite 4096 Jun 6 16:29 testing.git So my question is what am I missing here?

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  • Problem with running open office from the command line

    - by Devin Dixon
    Yesterday I installed OpenOffice on my Linux server. But when I go to run it through the command line, it says command cannot be found. I've also tried other things like OOWriter, etc. Has anyone had this problem? Installation process went like below: root@aserver [OOO330_m20_native_packed-1_en-US.9567/RPMS]# rpm -i *.rpm package openoffice.org-ure-1.7.0-9567.i586 is already installed package ooobasis3.3-core01-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-3.3.0-9567.i586 is already installed package ooobasis3.3-core02-3.3.0-9567.i586 is already installed package ooobasis3.3-core03-3.3.0-9567.i586 is already installed package ooobasis3.3-core04-3.3.0-9567.i586 is already installed package ooobasis3.3-core05-3.3.0-9567.i586 is already installed package ooobasis3.3-core06-3.3.0-9567.i586 is already installed package ooobasis3.3-core07-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-base-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-calc-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-draw-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-help-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-impress-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-math-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-res-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-writer-3.3.0-9567.i586 is already installed package ooobasis3.3-base-3.3.0-9567.i586 is already installed package ooobasis3.3-calc-3.3.0-9567.i586 is already installed package ooobasis3.3-draw-3.3.0-9567.i586 is already installed package ooobasis3.3-images-3.3.0-9567.i586 is already installed package openoffice.org3-3.3.0-9567.i586 is already installed package ooobasis3.3-impress-3.3.0-9567.i586 is already installed package ooobasis3.3-math-3.3.0-9567.i586 is already installed package ooobasis3.3-writer-3.3.0-9567.i586 is already installed package jre-1.6.0_22-fcs.i586 is already installed package ooobasis3.3-binfilter-3.3.0-9567.i586 is already installed package ooobasis3.3-en-US-binfilter-3.3.0-9567.i586 is already installed package ooobasis3.3-gnome-integration-3.3.0-9567.i586 is already installed package ooobasis3.3-graphicfilter-3.3.0-9567.i586 is already installed package ooobasis3.3-javafilter-3.3.0-9567.i586 is already installed package ooobasis3.3-kde-integration-3.3.0-9567.i586 is already installed package ooobasis3.3-onlineupdate-3.3.0-9567.i586 is already installed package ooobasis3.3-ooofonts-3.3.0-9567.i586 is already installed package ooobasis3.3-oooimprovement-3.3.0-9567.i586 is already installed package ooobasis3.3-ooolinguistic-3.3.0-9567.i586 is already installed package ooobasis3.3-pyuno-3.3.0-9567.i586 is already installed package ooobasis3.3-testtool-3.3.0-9567.i586 is already installed package ooobasis3.3-xsltfilter-3.3.0-9567.i586 is already installed package openoffice.org3-base-3.3.0-9567.i586 is already installed package openoffice.org3-calc-3.3.0-9567.i586 is already installed package openoffice.org3-dict-en-3.3.0-9567.i586 is already installed package openoffice.org3-dict-es-3.3.0-9567.i586 is already installed package openoffice.org3-dict-fr-3.3.0-9567.i586 is already installed package openoffice.org3-draw-3.3.0-9567.i586 is already installed package openoffice.org3-en-US-3.3.0-9567.i586 is already installed package openoffice.org3-impress-3.3.0-9567.i586 is already installed package openoffice.org3-math-3.3.0-9567.i586 is already installed package openoffice.org3-writer-3.3.0-9567.i586 is already installed root@aserver [OOO330_m20_native_p acked-1_en-US.9567/RPMS]# soffice bash: soffice: command not found

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  • mod_rewrite REQUEST_FILENAME doesn't contain absolute path

    - by Paul Dixon
    I have a problem with a file test operation in a mod_rewrite RewriteCond entry which is testing whether %{REQUEST_FILENAME} exists. It seems that rather than %{REQUEST_FILENAME} being an absolute path, I'm getting a path which is rooted at the DocumentRoot instead. Configuration I have this inside a <VirtualHost> block in my apache 2.2.9 configuration: RewriteEngine on RewriteLog /tmp/rewrite.log RewriteLogLevel 5 #push virtually everything through our dispatcher script RewriteCond %{REQUEST_FILENAME} !-f RewriteCond %{REQUEST_FILENAME} !-d RewriteRule ^/([^/]*)/?([^/]*) /dispatch.php?_c=$1&_m=$2 [qsa,L] Diagnostics attempted That rule is a common enough idiom for routing requests for non-existent files or directories through a script. Trouble is, it's firing even if a file does exist. If I remove the rule, I can request normal files just fine. But with the rule in place, these requests get directed to dispatch.php Rewrite log trace Here's what I see in the rewrite.log init rewrite engine with requested uri /test.txt applying pattern '^/([^/]*)/?([^/]*)' to uri '/test.txt' RewriteCond: input='/test.txt' pattern='!-f' => matched RewriteCond: input='/test.txt' pattern='!-d' => matched rewrite '/test.txt' -> '/dispatch.php?_c=test.txt&_m=' split uri=/dispatch.php?_c=test.txt&_m= -> uri=/dispatch.php, args=_c=test.txt&_m= local path result: /dispatch.php prefixed with document_root to /path/to/my/public_html/dispatch.php go-ahead with /path/to/my/public_html/dispatch.php [OK] So, it looks to me like the REQUEST_FILENAME is being presented as a path from the document root, rather than the file system root, which is presumably why the file test operator fails. Any pointers for resolving this gratefully received...

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  • Redirect To Domain Before SSL Is Read

    - by Devin Dixon
    I had to switch servers and I want to redirect all SSL urls to the non-ssl site. The problem I am running into is the https site still throws invalid certificate error even through apache has the redirect implemented. <VirtualHost *:443> ServerAdmin [email protected] DocumentRoot /data/sites/www.example.com/main/ RewriteEngine on Redirect 301 / http://www.example.com SSLEngine on SSLCertificateFile /etc/httpd/ssl/www.examplecom/ssl-cert-snakeoil.pem SSLCertificateKeyFile /etc/httpd/ssl/www.example.com/ssl-cert-snakeoil.key ServerName www.example.com ErrorLog "logs/example.com-error_log" CustomLog "logs/example.com-access_log" common </VirtualHost> My question is, how can I do a redirect and avoid the invalid ssl certifcation error in the browser?

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  • Windows XP volume control spontaneously slides to zero

    - by Paul Dixon
    Was listening to a podcast in iTunes at my desk, left my desk briefly and as I sat down, the volume faded. If I scrolled the volume back up, using my keyboard or the volume tray icon, it would smoothly scroll back down again. I rebooted, same thing occurred. Figuring maybe I had a stuck keyboard or hitherto undiscovered mouse function, I unplugged each in turn. Volume still wanted to go to zero! Anyone know what might cause this? It's driving me nuts!

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  • Keyboard window snap-to-position on Linux

    - by Chris Dixon
    I'm looking for a Linux utility that allows me to define arbitrary keyboard shortcuts that will move the frontmost window to a specific absolute position on-screen, depending on the shortcut. An OSX utility which does this is Breeze (http://autumnapps.com/breeze/ ) -- Is there a Linux equivalent?

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  • SQL SERVER – How to Recover SQL Database Data Deleted by Accident

    - by Pinal Dave
    In Repair a SQL Server database using a transaction log explorer, I showed how to use ApexSQL Log, a SQL Server transaction log viewer, to recover a SQL Server database after a disaster. In this blog, I’ll show you how to use another SQL Server disaster recovery tool from ApexSQL in a situation when data is accidentally deleted. You can download ApexSQL Recover here, install, and play along. With a good SQL Server disaster recovery strategy, data recovery is not a problem. You have a reliable full database backup with valid data, a full database backup and subsequent differential database backups, or a full database backup and a chain of transaction log backups. But not all situations are ideal. Here we’ll address some sub-optimal scenarios, where you can still successfully recover data. If you have only a full database backup This is the least optimal SQL Server disaster recovery strategy, as it doesn’t ensure minimal data loss. For example, data was deleted on Wednesday. Your last full database backup was created on Sunday, three days before the records were deleted. By using the full database backup created on Sunday, you will be able to recover SQL database records that existed in the table on Sunday. If there were any records inserted into the table on Monday or Tuesday, they will be lost forever. The same goes for records modified in this period. This method will not bring back modified records, only the old records that existed on Sunday. If you restore this full database backup, all your changes (intentional and accidental) will be lost and the database will be reverted to the state it had on Sunday. What you have to do is compare the records that were in the table on Sunday to the records on Wednesday, create a synchronization script, and execute it against the Wednesday database. If you have a full database backup followed by differential database backups Let’s say the situation is the same as in the example above, only you create a differential database backup every night. Use the full database backup created on Sunday, and the last differential database backup (created on Tuesday). In this scenario, you will lose only the data inserted and updated after the differential backup created on Tuesday. If you have a full database backup and a chain of transaction log backups This is the SQL Server disaster recovery strategy that provides minimal data loss. With a full chain of transaction logs, you can recover the SQL database to an exact point in time. To provide optimal results, you have to know exactly when the records were deleted, because restoring to a later point will not bring back the records. This method requires restoring the full database backup first. If you have any differential log backup created after the last full database backup, restore the most recent one. Then, restore transaction log backups, one by one, it the order they were created starting with the first created after the restored differential database backup. Now, the table will be in the state before the records were deleted. You have to identify the deleted records, script them and run the script against the original database. Although this method is reliable, it is time-consuming and requires a lot of space on disk. How to easily recover deleted records? The following solution enables you to recover SQL database records even if you have no full or differential database backups and no transaction log backups. To understand how ApexSQL Recover works, I’ll explain what happens when table data is deleted. Table data is stored in data pages. When you delete table records, they are not immediately deleted from the data pages, but marked to be overwritten by new records. Such records are not shown as existing anymore, but ApexSQL Recover can read them and create undo script for them. How long will deleted records stay in the MDF file? It depends on many factors, as time passes it’s less likely that the records will not be overwritten. The more transactions occur after the deletion, the more chances the records will be overwritten and permanently lost. Therefore, it’s recommended to create a copy of the database MDF and LDF files immediately (if you cannot take your database offline until the issue is solved) and run ApexSQL Recover on them. Note that a full database backup will not help here, as the records marked for overwriting are not included in the backup. First, I’ll delete some records from the Person.EmailAddress table in the AdventureWorks database.   I can delete these records in SQL Server Management Studio, or execute a script such as DELETE FROM Person.EmailAddress WHERE BusinessEntityID BETWEEN 70 AND 80 Then, I’ll start ApexSQL Recover and select From DELETE operation in the Recovery tab.   In the Select the database to recover step, first select the SQL Server instance. If it’s not shown in the drop-down list, click the Server icon right to the Server drop-down list and browse for the SQL Server instance, or type the instance name manually. Specify the authentication type and select the database in the Database drop-down list.   In the next step, you’re prompted to add additional data sources. As this can be a tricky step, especially for new users, ApexSQL Recover offers help via the Help me decide option.   The Help me decide option guides you through a series of questions about the database transaction log and advises what files to add. If you know that you have no transaction log backups or detached transaction logs, or the online transaction log file has been truncated after the data was deleted, select No additional transaction logs are available. If you know that you have transaction log backups that contain the delete transactions you want to recover, click Add transaction logs. The online transaction log is listed and selected automatically.   Click Add if to add transaction log backups. It would be best if you have a full transaction log chain, as explained above. The next step for this option is to specify the time range.   Selecting a small time range for the time of deletion will create the recovery script just for the accidentally deleted records. A wide time range might script the records deleted on purpose, and you don’t want that. If needed, you can check the script generated and manually remove such records. After that, for all data sources options, the next step is to select the tables. Be careful here, if you deleted some data from other tables on purpose, and don’t want to recover them, don’t select all tables, as ApexSQL Recover will create the INSERT script for them too.   The next step offers two options: to create a recovery script that will insert the deleted records back into the Person.EmailAddress table, or to create a new database, create the Person.EmailAddress table in it, and insert the deleted records. I’ll select the first one.   The recovery process is completed and 11 records are found and scripted, as expected.   To see the script, click View script. ApexSQL Recover has its own script editor, where you can review, modify, and execute the recovery script. The insert into statements look like: INSERT INTO Person.EmailAddress( BusinessEntityID, EmailAddressID, EmailAddress, rowguid, ModifiedDate) VALUES( 70, 70, N'[email protected]' COLLATE SQL_Latin1_General_CP1_CI_AS, 'd62c5b4e-c91f-403f-b630-7b7e0fda70ce', '20030109 00:00:00.000' ); To execute the script, click Execute in the menu.   If you want to check whether the records are really back, execute SELECT * FROM Person.EmailAddress WHERE BusinessEntityID BETWEEN 70 AND 80 As shown, ApexSQL Recover recovers SQL database data after accidental deletes even without the database backup that contains the deleted data and relevant transaction log backups. ApexSQL Recover reads the deleted data from the database data file, so this method can be used even for databases in the Simple recovery model. Besides recovering SQL database records from a DELETE statement, ApexSQL Recover can help when the records are lost due to a DROP TABLE, or TRUNCATE statement, as well as repair a corrupted MDF file that cannot be attached to as SQL Server instance. You can find more information about how to recover SQL database lost data and repair a SQL Server database on ApexSQL Solution center. There are solutions for various situations when data needs to be recovered. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • South Florida Code Camp 2010 &ndash; VI &ndash; 2010-02-27

    - by Dave Noderer
    Catching up after our sixth code camp here in the Ft Lauderdale, FL area. Website at: http://www.fladotnet.com/codecamp. For the 5th time, DeVry University hosted the event which makes everything else really easy! Statistics from 2010 South Florida Code Camp: 848 registered (we use Microsoft Group Events) ~ 600 attended (516 took name badges) 64 speakers (including speaker idol) 72 sessions 12 parallel tracks Food 400 waters 600 sodas 900 cups of coffee (it was cold!) 200 pounds of ice 200 pizza's 10 large salad trays 900 mouse pads Photos on facebook Dave Noderer: http://www.facebook.com/home.php#!/album.php?aid=190812&id=693530361 Joe Healy: http://www.facebook.com/devfish?ref=mf#!/album.php?aid=202787&id=720054950 Will Strohl:http://www.facebook.com/home.php#!/album.php?aid=2045553&id=1046966128&ref=mf Veronica Gonzalez: http://www.facebook.com/home.php#!/album.php?aid=150954&id=672439484 Florida Speaker Idol One of the sessions at code camp was the South Florida Regional speaker idol competition. After user group level competitions there are five competitors. I acted as MC and score keeper while Ed Hill, Bob O’Connell, John Dunagan and Shervin Shakibi were judges. This statewide competition is being run by Roy Lawsen in Lakeland and the winner, Jeff Truman from Naples will move on to the state finals to be held at the Orlando Code Camp on 3/27/2010: http://www.orlandocodecamp.com/. Each speaker has 10 minutes. The participants were: Alex Koval Jeff Truman Jared Nielsen Chris Catto Venkat Narayanasamy They all did a great job and I’m working with each to make sure they don’t stop there and start speaking at meetings. Thanks to everyone involved! Volunteers As always events like this don’t happen without a lot of help! The key people were: Ed Hill, Bob O’Connell – DeVry For the months leading up to the event, Ed collects all of the swag, books, etc and stores them. He holds meeting with various DeVry departments to coordinate the day, he works with the students in the days  before code camp to stuff bags, print signs, arrange tables and visit BJ’s for our supplies (I go and pay but have a small car!). And of course the day of the event he is there at 5:30 am!! We took two SUV’s to BJ’s, i was really worried that the 36 cases of water were going to break his rear axle! He also helps with the students and works very hard before and after the event. Rainer Haberman – Speakers and Volunteer of the Year Rainer has helped over the past couple of years but this time he took full control of arranging the tracks. I did some preliminary work solicitation speakers but he took over all communications after that. We have tried various organizations around speakers, chair per track, central team but having someone paying attention to the details is definitely the way to go! This was the first year I did not have to jump in at the last minute and re-arrange everything. There were lots of kudo’s from the speakers too saying they felt it was more organized than they have experienced in the past from any code camp. Thanks Rainer! Ray Alamonte – Book Swap We saw the idea of a book swap from the Alabama Code Camp and thought we would give it a try. Ray jumped in and took control. The idea was to get people to bring their old technical books to swap or for others to buy. You got a ticket for each book you brought that you could then turn in to buy another book. If you did not have a ticket you could buy a book for $1. Net proceeds were $153 which I rounded up and donated to the Red Cross. There is plenty going on in Haiti and Chile! I don’t think we really got a count of how many books came in. I many cases the books barely hit the table before being picked up again. At the end we were left with a dozen books which we donated to the DeVry library. A great success we will definitely do again! Jace Weiss / Ratchelen Hut – Coffee and Snacks Wow, this was an eye opener. In past years a few of us would struggle to give some attention to coffee, snacks, etc. But it was always tenuous and always ended up running out of coffee. In the past we have tried buying Dunkin Donuts coffee, renting urns, borrowing urns, etc. This year I actually purchased 2 – 100 cup Westbend commercial brewers plus a couple of small urns (30 and 60 cup we used for decaf). We got them both started early (although i forgot to push the on button on one!) and primed it with 10 boxes of Joe from Dunkin. then Jace and Rachelen took over.. once a batch was brewed they would refill the boxes, keep the area clean and at one point were filling cups. We never ran out of coffee and served a few hundred more than last  year. We did look but next year I’ll get a large insulated (like gatorade) dispensing container. It all went very smoothly and having help focused on that one area was a big win. Thanks Jace and Rachelen! Ken & Shirley Golding / Roberta Barbosa – Registration Ken & Shirley showed up and took over registration. This year we printed small name tags for everyone registered which was great because it is much easier to remember someone’s name when they are labeled! In any case it went the smoothest it has ever gone. All three were actively pulling people through the registration, answering questions, directing them to bags and information very quickly. I did not see that there was too big a line at any time. Thanks!! Scott Katarincic / Vishal Shukla – Website For the 3rd?? year in a row, Scott was in charge of the website starting in August or September when I start on code camp. He handles all the requests, makes changes to the site and admin. I think two years ago he wrote all the backend administration and tunes it and the website a bit but things are pretty stable. The only thing I do is put up the sponsors. It is a big pressure off of me!! Thanks Scott! Vishal jumped into the web end this year and created a new Silverlight agenda page to replace the old ajax page. We will continue to enhance this but it is definitely a good step forward! Thanks! Alex Funkhouser – T-shirts/Mouse pads/tables/sponsors Alex helps in many areas. He helps me bring in sponsors and handles all the logistics for t-shirts, sponsor tables and this year the mouse pads. He is also a key person to help promote the event as well not to mention the after after party which I did not attend and don’t want to know much about! Students There were a number of student volunteers but don’t have all of their names. But thanks to them, they stuffed bags, patrolled pizza and helped with moving things around. Sponsors We had a bunch of great sponsors which allowed us to feed people and give a way a lot of great swag. Our major sponsors of DeVry, Microsoft (both DPE and UGSS), Infragistics, Telerik, SQL Share (End to End, SQL Saturdays), and Interclick are very much appreciated. The other sponsors Applied Innovations (also supply code camp hosting), Ultimate Software (a great local SW company), Linxter (reliable cloud messaging we are lucky to have here!), Mediascend (a media startup), SoftwareFX (another local SW company we are happy to have back participating in CC), CozyRoc (if you do SSIS, check them out), Arrow Design (local DNN and Silverlight experts),Boxes and Arrows (a local SW consulting company) and Robert Half. One thing we did this year besides a t-shirt was a mouse pad. I like it because it will be around for a long time on many desks. After much investigation and years of using mouse pad’s I’ve determined that the 1/8” fabric top is the best and that is what we got!   So now I get a break for a few months before starting again!

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  • Big Data – Is Big Data Relevant to me? – Big Data Questionnaires – Guest Post by Vinod Kumar

    - by Pinal Dave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions of SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. I think the series from Pinal is a good one for anyone planning to start on Big Data journey from the basics. In my daily customer interactions this buzz of “Big Data” always comes up, I react generally saying – “Sir, do you really have a ‘Big Data’ problem or do you have a big Data problem?” Generally, there is a silence in the air when I ask this question. Data is everywhere in organizations – be it big data, small data, all data and for few it is bad data which is same as no data :). Wow, don’t discount me as someone who opposes “Big Data”, I am a big supporter as much as I am a critic of the abuse of this term by the people. In this post, I wanted to let my mind flow so that you can also think in the direction I want you to see these concepts. In any case, this is not an exhaustive dump of what is in my mind – but you will surely get the drift how I am going to question Big Data terms from customers!!! Is Big Data Relevant to me? Many of my customers talk to me like blank whiteboard with no idea – “why Big Data”. They want to jump into the bandwagon of technology and they want to decipher insights from their unexplored data a.k.a. unstructured data with structured data. So what are these industry scenario’s that come to mind? Here are some of them: Financials Fraud detection: Banks and Credit cards are monitoring your spending habits on real-time basis. Customer Segmentation: applies in every industry from Banking to Retail to Aviation to Utility and others where they deal with end customer who consume their products and services. Customer Sentiment Analysis: Responding to negative brand perception on social or amplify the positive perception. Sales and Marketing Campaign: Understand the impact and get closer to customer delight. Call Center Analysis: attempt to take unstructured voice recordings and analyze them for content and sentiment. Medical Reduce Re-admissions: How to build a proactive follow-up engagements with patients. Patient Monitoring: How to track Inpatient, Out-Patient, Emergency Visits, Intensive Care Units etc. Preventive Care: Disease identification and Risk stratification is a very crucial business function for medical. Claims fraud detection: There is no precise dollars that one can put here, but this is a big thing for the medical field. Retail Customer Sentiment Analysis, Customer Care Centers, Campaign Management. Supply Chain Analysis: Every sensors and RFID data can be tracked for warehouse space optimization. Location based marketing: Based on where a check-in happens retail stores can be optimize their marketing. Telecom Price optimization and Plans, Finding Customer churn, Customer loyalty programs Call Detail Record (CDR) Analysis, Network optimizations, User Location analysis Customer Behavior Analysis Insurance Fraud Detection & Analysis, Pricing based on customer Sentiment Analysis, Loyalty Management Agents Analysis, Customer Value Management This list can go on to other areas like Utility, Manufacturing, Travel, ITES etc. So as you can see, there are obviously interesting use cases for each of these industry verticals. These are just representative list. Where to start? A lot of times I try to quiz customers on a number of dimensions before starting a Big Data conversation. Are you getting the data you need the way you want it and in a timely manner? Can you get in and analyze the data you need? How quickly is IT to respond to your BI Requests? How easily can you get at the data that you need to run your business/department/project? How are you currently measuring your business? Can you get the data you need to react WITHIN THE QUARTER to impact behaviors to meet your numbers or is it always “rear-view mirror?” How are you measuring: The Brand Customer Sentiment Your Competition Your Pricing Your performance Supply Chain Efficiencies Predictive product / service positioning What are your key challenges of driving collaboration across your global business?  What the challenges in innovation? What challenges are you facing in getting more information out of your data? Note: Garbage-in is Garbage-out. Hold good for all reporting / analytics requirements Big Data POCs? A number of customers get into the realm of setting a small team to work on Big Data – well it is a great start from an understanding point of view, but I tend to ask a number of other questions to such customers. Some of these common questions are: To what degree is your advanced analytics (natural language processing, sentiment analysis, predictive analytics and classification) paired with your Big Data’s efforts? Do you have dedicated resources exploring the possibilities of advanced analytics in Big Data for your business line? Do you plan to employ machine learning technology while doing Advanced Analytics? How is Social Media being monitored in your organization? What is your ability to scale in terms of storage and processing power? Do you have a system in place to sort incoming data in near real time by potential value, data quality, and use frequency? Do you use event-driven architecture to manage incoming data? Do you have specialized data services that can accommodate different formats, security, and the management requirements of multiple data sources? Is your organization currently using or considering in-memory analytics? To what degree are you able to correlate data from your Big Data infrastructure with that from your enterprise data warehouse? Have you extended the role of Data Stewards to include ownership of big data components? Do you prioritize data quality based on the source system (that is Facebook/Twitter data has lower quality thresholds than radio frequency identification (RFID) for a tracking system)? Do your retention policies consider the different legal responsibilities for storing Big Data for a specific amount of time? Do Data Scientists work in close collaboration with Data Stewards to ensure data quality? How is access to attributes of Big Data being given out in the organization? Are roles related to Big Data (Advanced Analyst, Data Scientist) clearly defined? How involved is risk management in the Big Data governance process? Is there a set of documented policies regarding Big Data governance? Is there an enforcement mechanism or approach to ensure that policies are followed? Who is the key sponsor for your Big Data governance program? (The CIO is best) Do you have defined policies surrounding the use of social media data for potential employees and customers, as well as the use of customer Geo-location data? How accessible are complex analytic routines to your user base? What is the level of involvement with outside vendors and third parties in regard to the planning and execution of Big Data projects? What programming technologies are utilized by your data warehouse/BI staff when working with Big Data? These are some of the important questions I ask each customer who is actively evaluating Big Data trends for their organizations. These questions give you a sense of direction where to start, what to use, how to secure, how to analyze and more. Sign off Any Big data is analysis is incomplete without a compelling story. The best way to understand this is to watch Hans Rosling – Gapminder (2:17 to 6:06) videos about the third world myths. Don’t get overwhelmed with the Big Data buzz word, the destination to what your data speaks is important. In this blog post, we did not particularly look at any Big Data technologies. This is a set of questionnaire one needs to keep in mind as they embark their journey of Big Data. I did write some of the basics in my blog: Big Data – Big Hype yet Big Opportunity. Do let me know if these questions make sense?  Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

    - by Pinal Dave
    In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D:  S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or  SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand  the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

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  • Developer’s Life – Disaster Lessons – Notes from the Field #039

    - by Pinal Dave
    [Note from Pinal]: This is a 39th episode of Notes from the Field series. What is the best solution do you have when you encounter a disaster in your organization. Now many of you would answer that in this scenario you would have another standby machine or alternative which you will plug in. Now let me ask second question – What would you do if you as an individual faces disaster?  In this episode of the Notes from the Field series database expert Mike Walsh explains a very crucial issue we face in our career, which is not technical but more to relate to human nature. Read on this may be the best blog post you might read in recent times. Howdy! When it was my turn to share the Notes from the Field last time, I took a departure from my normal technical content to talk about Attitude and Communication.(http://blog.sqlauthority.com/2014/05/08/developers-life-attitude-and-communication-they-can-cause-problems-notes-from-the-field-027/) Pinal said it was a popular topic so I hope he won’t mind if I stick with Professional Development for another of my turns at sharing some information here. Like I said last time, the “soft skills” of the IT world are often just as important – sometimes more important – than the technical skills. As a consultant with Linchpin People – I see so many situations where the professional skills I’ve gained and use are more valuable to clients than knowing the best way to tune a query. Today I want to continue talking about professional development and tell you about the way I almost got myself hit by a train – and why that matters in our day jobs. Sometimes we can learn a lot from disasters. Whether we caused them or someone else did. If you are interested in learning about some of my observations in these lessons you can see more where I talk about lessons from disasters on my blog. For now, though, onto how I almost got my vehicle hit by a train… The Train Crash That Almost Was…. My family and I own a little schoolhouse building about a 10 mile drive away from our house. We use it as a free resource for families in the area that homeschool their children – so they can have some class space. I go up there a lot to check in on the property, to take care of the trash and to do work on the property. On the way there, there is a very small Stop Sign controlled railroad intersection. There is only two small freight trains a day passing there. Actually the same train, making a journey south and then back North. That’s it. This road is a small rural road, barely ever a second car driving in the neighborhood there when I am. The stop sign is pretty much there only for the train crossing. When we first bought the building, I was up there a lot doing renovations on the property. Being familiar with the area, I am also familiar with the train schedule and know the tracks are normally free of trains. So I developed a bad habit. You see, I’d approach the stop sign and slow down as I roll through it. Sometimes I’d do a quick look and come to an “almost” stop there but keep on going. I let my impatience and complacency take over. And that is because most of the time I was going there long after the train was done for the day or in between the runs. This habit became pretty well established after a couple years of driving the route. The behavior reinforced a bit by the success ratio. I saw others doing it as well from the neighborhood when I would happen to be there around the time another car was there. Well. You already know where this ends up by the title and backstory here. A few months ago I came to that little crossing, and I started to do the normal routine. I’d pretty much stopped looking in some respects because of the pattern I’d gotten into.  For some reason I looked and heard and saw the train slowly approaching and slammed on my brakes and stopped. It was an abrupt stop, and it was close. I probably would have made it okay, but I sat there thinking about lessons for IT professionals from the situation once I started breathing again and watched the cars loaded with sand and propane slowly labored down the tracks… Here are Those Lessons… It’s easy to get stuck into a routine – That isn’t always bad. Except when it’s a bad routine. Momentum and inertia are powerful. Once you have a habit and a routine developed – it’s really hard to break that. Make sure you are setting the right routines and habits TODAY. What almost dangerous things are you doing today? How are you almost messing up your production environment today? Stop doing that. Be Deliberate – (Even when you are the only one) – Like I said – a lot of people roll through that stop sign. Perhaps the neighbors or other drivers think “why is he fully stopping and looking… The train only comes two times a day!” – they can think that all they want. Through deliberate actions and forcing myself to pay attention, I will avoid that oops again. Slow down. Take a deep breath. Be Deliberate in your job. Pay attention to the small stuff and go out of your way to be careful. It will save you later. Be Observant – Keep your eyes open. By looking around, observing the situation and understanding what your servers, databases, users and vendors are doing – you’ll notice when something is out of place. But if you don’t know what is normal, if you don’t look to make sure nothing has changed – that train will come and get you. Where can you be more observant? What warning signs are you ignoring in your environment today? In the IT world – trains are everywhere. Projects move fast. Decisions happen fast. Problems turn from a warning sign to a disaster quickly. If you get stuck in a complacent pattern of “Everything is okay, it always has been and always will be” – that’s the time that you will most likely get stuck in a bad situation. Don’t let yourself get complacent, don’t let your team get complacent. That will lead to being proactive. And a proactive environment spends less money on consultants for troubleshooting problems you should have seen ahead of time. You can spend your money and IT budget on improving for your customers. If you want to get started with performance analytics and triage of virtualized SQL Servers with the help of experts, read more over at Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Weekly Series – Memory Lane – #051

    - by Pinal Dave
    Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Explanation and Understanding NOT NULL Constraint NOT NULL is integrity CONSTRAINT. It does not allow creating of the row where column contains NULL value. Most discussed questions about NULL is what is NULL? I will not go in depth analysis it. Simply put NULL is unknown or missing data. When NULL is present in database columns, it can affect the integrity of the database. I really do not prefer NULL in the database unless they are absolutely necessary. Three T-SQL Script to Create Primary Keys on Table I have always enjoyed writing about three topics Constraint and Keys, Backup and Restore and Datetime Functions. Primary Keys constraints prevent duplicate values for columns and provides a unique identifier to each column, as well it creates clustered index on the columns. 2008 Get Numeric Value From Alpha Numeric String – UDF for Get Numeric Numbers Only SQL is great with String operations. Many times, I use T-SQL to do my string operation. Let us see User Defined Function, which I wrote a few days ago, which will return only Numeric values from Alpha Numeric values. Introduction and Example of UNION and UNION ALL It is very much interesting when I get requests from blog reader to re-write my previous articles. I have received few requests to rewrite my article SQL SERVER – Union vs. Union All – Which is better for performance? with examples. I request you to read my previous article first to understand what is the concept and read this article to understand the same concept with an example. Downgrade Database for Previous Version The main questions is how they can downgrade the from SQL Server 2005 to SQL Server 2000? The answer is : Not Possible. Get Common Records From Two Tables Without Using Join Following is my scenario, Suppose Table 1 and Table 2 has same column e.g. Column1 Following is the query, 1. Select column1,column2 From Table1 2. Select column1 From Table2 I want to find common records from these tables, but I don’t want to use the Join clause because for that I need to specify the column name for Join condition. Will you help me to get common records without using Join condition? I am using SQL Server 2005. Retrieve – Select Only Date Part From DateTime – Best Practice – Part 2 A year ago I wrote a post about SQL SERVER – Retrieve – Select Only Date Part From DateTime – Best Practice where I have discussed two different methods of getting the date part from datetime. Introduction to CLR – Simple Example of CLR Stored Procedure CLR is an abbreviation of Common Language Runtime. In SQL Server 2005 and later version of it database objects can be created which are created in CLR. Stored Procedures, Functions, Triggers can be coded in CLR. CLR is faster than T-SQL in many cases. CLR is mainly used to accomplish tasks which are not possible by T-SQL or can use lots of resources. The CLR can be usually implemented where there is an intense string operation, thread management or iteration methods which can be complicated for T-SQL. Implementing CLR provides more security to the Extended Stored Procedure. 2009 Comic Slow Query – SQL Joke Before Presentation After Presentation Enable Automatic Statistic Update on Database In one of the recent projects, I found out that despite putting good indexes and optimizing the query, I could not achieve an optimized performance and I still received an unoptimized response from the SQL Server. On examination, I figured out that the culprit was statistics. The database that I was trying to optimize had auto update of the statistics was disabled. Recently Executed T-SQL Query Please refer to blog post  query to recently executed T-SQL query on database. Change Collation of Database Column – T-SQL Script – Consolidating Collations – Extention Script At some time in your DBA career, you may find yourself in a position when you sit back and realize that your database collations have somehow run amuck, or are faced with the ever annoying CANNOT RESOLVE COLLATION message when trying to join data of varying collation settings. 2010 Visiting Alma Mater – Delivering Session on Database Performance and Career – Nirma Institute of Technology Everyone always dreams of visiting their school and college, where they have studied once. It is a great feeling to see the college once again – where you have spent the wonderful golden years of your time. College time is filled with studies, education, emotions and several plans to build a future. I consider myself fortunate as I got the opportunity to study at some of the best places in the world. Change Column DataTypes There are times when I feel like writing that I am a day older in SQL Server. In fact, there are many who are looking for a solution that is simple enough. Have you ever searched online for something very simple. I often do and enjoy doing things which are straight forward and easy to change. 2011 Three DMVs – sys.dm_server_memory_dumps – sys.dm_server_services – sys.dm_server_registry In this blog post we will see three new DMVs which are introduced in Denali. The DMVs are very simple and there is not much to describe them. So here is the simple game. I will be asking a question back to you after seeing the result of the each of the DMV and you help me to complete this blog post. A Simple Quiz – T-SQL Brain Trick If you have some time, I strongly suggest you try this quiz out as it is for sure twists your brain. 2012 List All The Column With Specific Data Types in Database 5 years ago I wrote script SQL SERVER – 2005 – List All The Column With Specific Data Types, when I read it again, it is very much relevant and I liked it. This is one of the script which every developer would like to keep it handy. I have upgraded the script bit more. I have included few additional information which I believe I should have added from the beginning. It is difficult to visualize the final script when we are writing it first time. Find First Non-Numeric Character from String The function PATINDEX exists for quite a long time in SQL Server but I hardly see it being used. Well, at least I use it and I am comfortable using it. Here is a simple script which I use when I have to identify first non-numeric character. Finding Different ColumnName From Almost Identitical Tables Well here is the interesting example of how we can use sys.column catalogue views and get the details of the newly added column. I have previously written about EXCEPT over here which is very similar to MINUS of Oracle. Storing Data and Files in Cloud – Dropbox – Personal Technology Tip I thought long and hard about doing a Personal Technology Tips series for this blog.  I have so many tips I’d like to share.  I am on my computer almost all day, every day, so I have a treasure trove of interesting tidbits I like to share if given the chance.  The only thing holding me back – which tip to share first?  The first tip obviously has the weight of seeming like the most important.  But this would mean choosing amongst my favorite tricks and shortcuts.  This is a hard task. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • MySQL – Scalability on Amazon RDS: Scale out to multiple RDS instances

    - by Pinal Dave
    Today, I’d like to discuss getting better MySQL scalability on Amazon RDS. The question of the day: “What can you do when a MySQL database needs to scale write-intensive workloads beyond the capabilities of the largest available machine on Amazon RDS?” Let’s take a look. In a typical EC2/RDS set-up, users connect to app servers from their mobile devices and tablets, computers, browsers, etc.  Then app servers connect to an RDS instance (web/cloud services) and in some cases they might leverage some read-only replicas.   Figure 1. A typical RDS instance is a single-instance database, with read replicas.  This is not very good at handling high write-based throughput. As your application becomes more popular you can expect an increasing number of users, more transactions, and more accumulated data.  User interactions can become more challenging as the application adds more sophisticated capabilities. The result of all this positive activity: your MySQL database will inevitably begin to experience scalability pressures. What can you do? Broadly speaking, there are four options available to improve MySQL scalability on RDS. 1. Larger RDS Instances – If you’re not already using the maximum available RDS instance, you can always scale up – to larger hardware.  Bigger CPUs, more compute power, more memory et cetera. But the largest available RDS instance is still limited.  And they get expensive. “High-Memory Quadruple Extra Large DB Instance”: 68 GB of memory 26 ECUs (8 virtual cores with 3.25 ECUs each) 64-bit platform High I/O Capacity Provisioned IOPS Optimized: 1000Mbps 2. Provisioned IOPs – You can get provisioned IOPs and higher throughput on the I/O level. However, there is a hard limit with a maximum instance size and maximum number of provisioned IOPs you can buy from Amazon and you simply cannot scale beyond these hardware specifications. 3. Leverage Read Replicas – If your application permits, you can leverage read replicas to offload some reads from the master databases. But there are a limited number of replicas you can utilize and Amazon generally requires some modifications to your existing application. And read-replicas don’t help with write-intensive applications. 4. Multiple Database Instances – Amazon offers a fourth option: “You can implement partitioning,thereby spreading your data across multiple database Instances” (Link) However, Amazon does not offer any guidance or facilities to help you with this. “Multiple database instances” is not an RDS feature.  And Amazon doesn’t explain how to implement this idea. In fact, when asked, this is the response on an Amazon forum: Q: Is there any documents that describe the partition DB across multiple RDS? I need to use DB with more 1TB but exist a limitation during the create process, but I read in the any FAQ that you need to partition database, but I don’t find any documents that describe it. A: “DB partitioning/sharding is not an official feature of Amazon RDS or MySQL, but a technique to scale out database by using multiple database instances. The appropriate way to split data depends on the characteristics of the application or data set. Therefore, there is no concrete and specific guidance.” So now what? The answer is to scale out with ScaleBase. Amazon RDS with ScaleBase: What you get – MySQL Scalability! ScaleBase is specifically designed to scale out a single MySQL RDS instance into multiple MySQL instances. Critically, this is accomplished with no changes to your application code.  Your application continues to “see” one database.   ScaleBase does all the work of managing and enforcing an optimized data distribution policy to create multiple MySQL instances. With ScaleBase, data distribution, transactions, concurrency control, and two-phase commit are all 100% transparent and 100% ACID-compliant, so applications, services and tooling continue to interact with your distributed RDS as if it were a single MySQL instance. The result: now you can cost-effectively leverage multiple MySQL RDS instance to scale out write-intensive workloads to an unlimited number of users, transactions, and data. Amazon RDS with ScaleBase: What you keep – Everything! And how does this change your Amazon environment? 1. Keep your application, unchanged – There is no change your application development life-cycle at all.  You still use your existing development tools, frameworks and libraries.  Application quality assurance and testing cycles stay the same. And, critically, you stay with an ACID-compliant MySQL environment. 2. Keep your RDS value-added services – The value-added services that you rely on are all still available. Amazon will continue to handle database maintenance and updates for you. You can still leverage High Availability via Multi A-Z.  And, if it benefits youra application throughput, you can still use read replicas. 3. Keep your RDS administration – Finally the RDS monitoring and provisioning tools you rely on still work as they did before. With your one large MySQL instance, now split into multiple instances, you can actually use less expensive, smallersmaller available RDS hardware and continue to see better database performance. Conclusion Amazon RDS is a tremendous service, but it doesn’t offer solutions to scale beyond a single MySQL instance. Larger RDS instances get more expensive.  And when you max-out on the available hardware, you’re stuck.  Amazon recommends scaling out your single instance into multiple instances for transaction-intensive apps, but offers no services or guidance to help you. This is where ScaleBase comes in to save the day. It gives you a simple and effective way to create multiple MySQL RDS instances, while removing all the complexities typically caused by “DIY” sharding andwith no changes to your applications . With ScaleBase you continue to leverage the AWS/RDS ecosystem: commodity hardware and value added services like read replicas, multi A-Z, maintenance/updates and administration with monitoring tools and provisioning. SCALEBASE ON AMAZON If you’re curious to try ScaleBase on Amazon, it can be found here – Download NOW. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: MySQL, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL – Migrate Database from SQL Server to NuoDB – A Quick Tutorial

    - by Pinal Dave
    Data is growing exponentially and every organization with growing data is thinking of next big innovation in the world of Big Data. Big data is a indeed a future for every organization at one point of the time. Just like every other next big thing, big data has its own challenges and issues. The biggest challenge associated with the big data is to find the ideal platform which supports the scalability and growth of the data. If you are a regular reader of this blog, you must be familiar with NuoDB. I have been working with NuoDB for a while and their recent release is the best thus far. NuoDB is an elastically scalable SQL database that can run on local host, datacenter and cloud-based resources. A key feature of the product is that it does not require sharding (read more here). Last week, I was able to install NuoDB in less than 90 seconds and have explored their Explorer and Admin sections. You can read about my experiences in these posts: SQL – Step by Step Guide to Download and Install NuoDB – Getting Started with NuoDB SQL – Quick Start with Admin Sections of NuoDB – Manage NuoDB Database SQL – Quick Start with Explorer Sections of NuoDB – Query NuoDB Database Many SQL Authority readers have been following me in my journey to evaluate NuoDB. One of the frequently asked questions I’ve received from you is if there is any way to migrate data from SQL Server to NuoDB. The fact is that there is indeed a way to do so and NuoDB provides a fantastic tool which can help users to do it. NuoDB Migrator is a command line utility that supports the migration of Microsoft SQL Server, MySQL, Oracle, and PostgreSQL schemas and data to NuoDB. The migration to NuoDB is a three-step process: NuoDB Migrator generates a schema for a target NuoDB database It loads data into the target NuoDB database It dumps data from the source database Let’s see how we can migrate our data from SQL Server to NuoDB using a simple three-step approach. But before we do that we will create a sample database in MSSQL and later we will migrate the same database to NuoDB: Setup Step 1: Build a sample data CREATE DATABASE [Test]; CREATE TABLE [Department]( [DepartmentID] [smallint] NOT NULL, [Name] VARCHAR(100) NOT NULL, [GroupName] VARCHAR(100) NOT NULL, [ModifiedDate] [datetime] NOT NULL, CONSTRAINT [PK_Department_DepartmentID] PRIMARY KEY CLUSTERED ( [DepartmentID] ASC ) ) ON [PRIMARY]; INSERT INTO Department SELECT * FROM AdventureWorks2012.HumanResources.Department; Note that I am using the SQL Server AdventureWorks database to build this sample table but you can build this sample table any way you prefer. Setup Step 2: Install Java 64 bit Before you can begin the migration process to NuoDB, make sure you have 64-bit Java installed on your computer. This is due to the fact that the NuoDB Migrator tool is built in Java. You can download 64-bit Java for Windows, Mac OSX, or Linux from the following link: http://java.com/en/download/manual.jsp. One more thing to remember is that you make sure that the path in your environment settings is set to your JAVA_HOME directory or else the tool will not work. Here is how you can do it: Go to My Computer >> Right Click >> Select Properties >> Click on Advanced System Settings >> Click on Environment Variables >> Click on New and enter the following values. Variable Name: JAVA_HOME Variable Value: C:\Program Files\Java\jre7 Make sure you enter your Java installation directory in the Variable Value field. Setup Step 3: Install JDBC driver for SQL Server. There are two JDBC drivers available for SQL Server.  Select the one you prefer to use by following one of the two links below: Microsoft JDBC Driver jTDS JDBC Driver In this example we will be using jTDS JDBC driver. Once you download the driver, move the driver to your NuoDB installation folder. In my case, I have moved the JAR file of the driver into the C:\Program Files\NuoDB\tools\migrator\jar folder as this is my NuoDB installation directory. Now we are all set to start the three-step migration process from SQL Server to NuoDB: Migration Step 1: NuoDB Schema Generation Here is the command I use to generate a schema of my SQL Server Database in NuoDB. First I go to the folder C:\Program Files\NuoDB\tools\migrator\bin and execute the nuodb-migrator.bat file. Note that my database name is ‘test’. Additionally my username and password is also ‘test’. You can see that my SQL Server database is running on my localhost on port 1433. Additionally, the schema of the table is ‘dbo’. nuodb-migrator schema –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.path=/tmp/schema.sql The above script will generate a schema of all my SQL Server tables and will put it in the folder C:\tmp\schema.sql . You can open the schema.sql file and execute this file directly in your NuoDB instance. You can follow the link here to see how you can execute the SQL script in NuoDB. Please note that if you have not yet created the schema in the NuoDB database, you should create it before executing this step. Step 2: Generate the Dump File of the Data Once you have recreated your schema in NuoDB from SQL Server, the next step is very easy. Here we create a CSV format dump file, which will contain all the data from all the tables from the SQL Server database. The command to do so is very similar to the above command. Be aware that this step may take a bit of time based on your database size. nuodb-migrator dump –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.type=csv –output.path=/tmp/dump.cat Once the above command is successfully executed you can find your CSV file in the C:\tmp\ folder. However, you do not have to do anything manually. The third and final step will take care of completing the migration process. Migration Step 3: Load the Data into NuoDB After building schema and taking a dump of the data, the very next step is essential and crucial. It will take the CSV file and load it into the NuoDB database. nuodb-migrator load –target.url=jdbc:com.nuodb://localhost:48004/mytest –target.schema=dbo –target.username=test –target.password=test –input.path=/tmp/dump.cat Please note that in the above script we are now targeting the NuoDB database, which we have already created with the name of “MyTest”. If the database does not exist, create it manually before executing the above script. I have kept the username and password as “test”, but please make sure that you create a more secure password for your database for security reasons. Voila!  You’re Done That’s it. You are done. It took 3 setup and 3 migration steps to migrate your SQL Server database to NuoDB.  You can now start exploring the database and build excellent, scale-out applications. In this blog post, I have done my best to come up with simple and easy process, which you can follow to migrate your app from SQL Server to NuoDB. Download NuoDB I strongly encourage you to download NuoDB and go through my 3-step migration tutorial from SQL Server to NuoDB. Additionally here are two very important blog post from NuoDB CTO Seth Proctor. He has written excellent blog posts on the concept of the Administrative Domains. NuoDB has this concept of an Administrative Domain, which is a collection of hosts that can run one or multiple databases.  Each database has its own TEs and SMs, but all are managed within the Admin Console for that particular domain. http://www.nuodb.com/techblog/2013/03/11/getting-started-provisioning-a-domain/ http://www.nuodb.com/techblog/2013/03/14/getting-started-running-a-database/ Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: NuoDB

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  • Developer’s Life – Attitude and Communication – They Can Cause Problems – Notes from the Field #027

    - by Pinal Dave
    [Note from Pinal]: This is a 27th episode of Notes from the Field series. The biggest challenge for anyone is to understand human nature. We human have so many things on our mind at any moment of time. There are cases when what we say is not what we mean and there are cases where what we mean we do not say. We do say and things as per our mood and our agenda in mind. Sometimes there are incidents when our attitude creates confusion in the communication and we end up creating a situation which is absolutely not warranted. In this episode of the Notes from the Field series database expert Mike Walsh explains a very crucial issue we face in our career, which is not technical but more to relate to human nature. Read on this may be the best blog post you might read in recent times. In this week’s note from the field, I’m taking a slight departure from technical knowledge and concepts explained. We’ll be back to it next week, I’m sure. Pinal wanted us to explain some of the issues we bump into and how we see some of our customers arrive at problem situations and how we have helped get them back on the right track. Often it is a technical problem we are officially solving – but in a lot of cases as a consultant, we are really helping fix some communication difficulties. This is a technical blog post and not an “advice column” in a newspaper – but the longer I am a consultant, the more years I add to my experience in technology the more I learn that the vast majority of the problems we encounter have “soft skills” included in the chain of causes for the issue we are helping overcome. This is not going to be exhaustive but I hope that sharing four pieces of advice inspired by real issues starts a process of searching for places where we can be the cause of these challenges and look at fixing them in ourselves. Or perhaps we can begin looking at resolving them in teams that we manage. I’ll share three statements that I’ve either heard, read or said and talk about some of the communication or attitude challenges highlighted by the statement. 1 – “But that’s the SAN Administrator’s responsibility…” I heard that early on in my consulting career when talking with a customer who had serious corruption and no good recent backups – potentially no good backups at all. The statement doesn’t have to be this one exactly, but the attitude here is an attitude of “my job stops here, and I don’t care about the intent or principle of why I’m here.” It’s also a situation of having the attitude that as long as there is someone else to blame, I’m fine…  You see in this case, the DBA had a suspicion that the backups were not being handled right.  They were the DBA and they knew that they had responsibility to ensure SQL backups were good to go – it’s a basic requirement of a production DBA. In my “As A DBA Where Do I start?!” presentation, I argue that is job #1 of a DBA. But in this case, the thought was that there was someone else to blame. Rather than create extra work and take on responsibility it was decided to just let it be another team’s responsibility. This failed the company, the company’s customers and no one won. As technologists – we should strive to go the extra mile. If there is a lack of clarity around roles and responsibilities and we know it – we should push to get it resolved. Especially as the DBAs who should act as the advocates of the data contained in the databases we are responsible for. 2 – “We’ve always done it this way, it’s never caused a problem before!” Complacency. I have to say that many failures I’ve been paid good money to help recover from would have not happened had it been for an attitude of complacency. If any thoughts like this have entered your mind about your situation you may be suffering from it. If, while reading this, you get this sinking feeling in your stomach about that one thing you know should be fixed but haven’t done it.. Why don’t you stop and go fix it then come back.. “We should have better backups, but we’re on a SAN so we should be fine really.” “Technically speaking that could happen, but what are the chances?” “We’ll just clean that up as a fast follow” ..and so on. In the age of tightening IT budgets, increased expectations of up time, availability and performance there is no room for complacency. Our customers and business units expect – no demand – the best. Complacency says “we will give you second best or hopefully good enough and we accept the risk and know this may hurt us later. Sometimes an organization will opt for “good enough” and I agree with the concept that at times the perfect can be the enemy of the good. But when we make those decisions in a vacuum and are not reporting them up and discussing them as an organization that is different. That is us unilaterally choosing to do something less than the best and purposefully playing a game of chance. 3 – “This device must accept interference from other devices but not create any” I’ve paraphrased this one – but it’s something the Federal Communications Commission – a federal agency in the United States that regulates electronic communication – requires of all manufacturers of any device that could cause or receive interference electronically. I blogged in depth about this here (http://www.straightpathsql.com/archives/2011/07/relationship-advice-from-the-fcc/) so I won’t go into much detail other than to say this… If we all operated more on the premise that we should do our best to not be the cause of conflict, and to be less easily offended and less upset when we perceive offense life would be easier in many areas! This doesn’t always cause the issues we are called in to help out. Not directly. But where we see it is in unhealthy relationships between the various technology teams at a client. We’ll see teams hoarding knowledge, not sharing well with others and almost working against other teams instead of working with them. If you trace these problems back far enough it often stems from someone or some group of people violating this principle from the FCC. To Sum It Up Technology problems are easy to solve. At Linchpin People we help many customers get past the toughest technological challenge – and at the end of the day it is really just a repeatable process of pattern based troubleshooting, logical thinking and starting at the beginning and carefully stepping through to the end. It’s easy at the end of the day. The tough part of what we do as consultants is the people skills. Being able to help get teams working together, being able to help teams take responsibility, to improve team to team communication? That is the difficult part, and we get to use the soft skills on every engagement. Work on professional development (http://professionaldevelopment.sqlpass.org/) and see continuing improvement here, not just with technology. I can teach just about anyone how to be an excellent DBA and performance tuner, but some of these soft skills are much more difficult to teach. If you want to get started with performance analytics and triage of virtualized SQL Servers with the help of experts, read more over at Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – SSMS: Disk Usage Report

    - by Pinal Dave
    Let us start with humor!  I think we the series on various reports, we come to a logical point. We covered all the reports at server level. This means the reports we saw were targeted towards activities that are related to instance level operations. These are mostly like how a doctor diagnoses a patient. At this point I am reminded of a dialog which I read somewhere: Patient: Doc, It hurts when I touch my head. Doc: Ok, go on. What else have you experienced? Patient: It hurts even when I touch my eye, it hurts when I touch my arms, it even hurts when I touch my feet, etc. Doc: Hmmm … Patient: I feel it hurts when I touch anywhere in my body. Doc: Ahh … now I get it. You need a plaster to your finger John. Sometimes the server level gives an indicator to what is happening in the system, but we need to get to the root cause for a specific database. So, this is the first blog in series where we would start discussing about database level reports. To launch database level reports, expand selected server in Object Explorer, expand the Databases folder, and then right-click any database for which we want to look at reports. From the menu, select Reports, then Standard Reports, and then any of database level reports. In this blog, we would talk about four “disk” reports because they are similar: Disk Usage Disk Usage by Top Tables Disk Usage by Table Disk Usage by Partition Disk Usage This report shows multiple information about the database. Let us discuss them one by one.  We have divided the output into 5 different sections. Section 1 shows the high level summary of the database. It shows the space used by database files (mdf and ldf). Under the hood, the report uses, various DMVs and DBCC Commands, it is using sys.data_spaces and DBCC SHOWFILESTATS. Section 2 and 3 are pie charts. One for data file allocation and another for the transaction log file. Pie chart for “Data Files Space Usage (%)” shows space consumed data, indexes, allocated to the SQL Server database, and unallocated space which is allocated to the SQL Server database but not yet filled with anything. “Transaction Log Space Usage (%)” used DBCC SQLPERF (LOGSPACE) and shows how much empty space we have in the physical transaction log file. Section 4 shows the data from Default Trace and looks at Event IDs 92, 93, 94, 95 which are for “Data File Auto Grow”, “Log File Auto Grow”, “Data File Auto Shrink” and “Log File Auto Shrink” respectively. Here is an expanded view for that section. If default trace is not enabled, then this section would be replaced by the message “Trace Log is disabled” as highlighted below. Section 5 of the report uses DBCC SHOWFILESTATS to get information. Here is the enhanced version of that section. This shows the physical layout of the file. In case you have In-Memory Objects in the database (from SQL Server 2014), then report would show information about those as well. Here is the screenshot taken for a different database, which has In-Memory table. I have highlighted new things which are only shown for in-memory database. The new sections which are highlighted above are using sys.dm_db_xtp_checkpoint_files, sys.database_files and sys.data_spaces. The new type for in-memory OLTP is ‘FX’ in sys.data_space. The next set of reports is targeted to get information about a table and its storage. These reports can answer questions like: Which is the biggest table in the database? How many rows we have in table? Is there any table which has a lot of reserved space but its unused? Which partition of the table is having more data? Disk Usage by Top Tables This report provides detailed data on the utilization of disk space by top 1000 tables within the Database. The report does not provide data for memory optimized tables. Disk Usage by Table This report is same as earlier report with few difference. First Report shows only 1000 rows First Report does order by values in DMV sys.dm_db_partition_stats whereas second one does it based on name of the table. Both of the reports have interactive sort facility. We can click on any column header and change the sorting order of data. Disk Usage by Partition This report shows the distribution of the data in table based on partition in the table. This is so similar to previous output with the partition details now. Here is the query taken from profiler. SELECT row_number() OVER (ORDER BY a1.used_page_count DESC, a1.index_id) AS row_number ,      (dense_rank() OVER (ORDER BY a5.name, a2.name))%2 AS l1 ,      a1.OBJECT_ID ,      a5.name AS [schema] ,       a2.name ,       a1.index_id ,       a3.name AS index_name ,       a3.type_desc ,       a1.partition_number ,       a1.used_page_count * 8 AS total_used_pages ,       a1.reserved_page_count * 8 AS total_reserved_pages ,       a1.row_count FROM sys.dm_db_partition_stats a1 INNER JOIN sys.all_objects a2  ON ( a1.OBJECT_ID = a2.OBJECT_ID) AND a1.OBJECT_ID NOT IN (SELECT OBJECT_ID FROM sys.tables WHERE is_memory_optimized = 1) INNER JOIN sys.schemas a5 ON (a5.schema_id = a2.schema_id) LEFT OUTER JOIN  sys.indexes a3  ON ( (a1.OBJECT_ID = a3.OBJECT_ID) AND (a1.index_id = a3.index_id) ) WHERE (SELECT MAX(DISTINCT partition_number) FROM sys.dm_db_partition_stats a4 WHERE (a4.OBJECT_ID = a1.OBJECT_ID)) >= 1 AND a2.TYPE <> N'S' AND  a2.TYPE <> N'IT' ORDER BY a5.name ASC, a2.name ASC, a1.index_id, a1.used_page_count DESC, a1.partition_number Using all of the above reports, you should be able to get the usage of database files and also space used by tables. I think this is too much disk information for a single blog and I hope you have used them in the past to get data. Do let me know if you found anything interesting using these reports in your environments. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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  • SQL SERVER – Weekly Series – Memory Lane – #035

    - by Pinal Dave
    Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Row Overflow Data Explanation  In SQL Server 2005 one table row can contain more than one varchar(8000) fields. One more thing, the exclusions has exclusions also the limit of each individual column max width of 8000 bytes does not apply to varchar(max), nvarchar(max), varbinary(max), text, image or xml data type columns. Comparison Index Fragmentation, Index De-Fragmentation, Index Rebuild – SQL SERVER 2000 and SQL SERVER 2005 An old but like a gold article. Talks about lots of concepts related to Index and the difference from earlier version to the newer version. I strongly suggest that everyone should read this article just to understand how SQL Server has moved forward with the technology. Improvements in TempDB SQL Server 2005 had come up with quite a lots of improvements and this blog post describes them and explains the same. If you ask me what is my the most favorite article from early career. I must point out to this article as when I wrote this one I personally have learned a lot of new things. Recompile All The Stored Procedure on Specific TableI prefer to recompile all the stored procedure on the table, which has faced mass insert or update. sp_recompiles marks stored procedures to recompile when they execute next time. This blog post explains the same with the help of a script.  2008 SQLAuthority Download – SQL Server Cheatsheet You can download and print this cheat sheet and use it for your personal reference. If you have any suggestions, please let me know and I will see if I can update this SQL Server cheat sheet. Difference Between DBMS and RDBMS What is the difference between DBMS and RDBMS? DBMS – Data Base Management System RDBMS – Relational Data Base Management System or Relational DBMS High Availability – Hot Add Memory Hot Add CPU and Hot Add Memory are extremely interesting features of the SQL Server, however, personally I have not witness them heavily used. These features also have few restriction as well. I blogged about them in detail. 2009 Delete Duplicate Rows I have demonstrated in this blog post how one can identify and delete duplicate rows. Interesting Observation of Logon Trigger On All Servers – Solution The question I put forth in my previous article was – In single login why the trigger fires multiple times; it should be fired only once. I received numerous answers in thread as well as in my MVP private news group. Now, let us discuss the answer for the same. The answer is – It happens because multiple SQL Server services are running as well as intellisense is turned on. Blog post demonstrates how we can do the same with the help of SQL scripts. Management Studio New Features I have selected my favorite 5 features and blogged about it. IntelliSense for Query Editing Multi Server Query Query Editor Regions Object Explorer Enhancements Activity Monitors Maximum Number of Index per Table One of the questions I asked in my user group was – What is the maximum number of Index per table? I received lots of answers to this question but only two answers are correct. Let us now take a look at them in this blog post. 2010 Default Statistics on Column – Automatic Statistics on Column The truth is, Statistics can be in a table even though there is no Index in it. If you have the auto- create and/or auto-update Statistics feature turned on for SQL Server database, Statistics will be automatically created on the Column based on a few conditions. Please read my previously posted article, SQL SERVER – When are Statistics Updated – What triggers Statistics to Update, for the specific conditions when Statistics is updated. 2011 T-SQL Scripts to Find Maximum between Two Numbers In this blog post there are two different scripts listed which demonstrates way to find the maximum number between two numbers. I need your help, which one of the script do you think is the most accurate way to find maximum number? Find Details for Statistics of Whole Database – DMV – T-SQL Script I was recently asked is there a single script which can provide all the necessary details about statistics for any database. This question made me write following script. I was initially planning to use sp_helpstats command but I remembered that this is marked to be deprecated in future. 2012 Introduction to Function SIGN SIGN Function is very fundamental function. It will return the value 1, -1 or 0. If your value is negative it will return you negative -1 and if it is positive it will return you positive +1. Let us start with a simple small example. Template Browser – A Very Important and Useful Feature of SSMS Templates are like a quick cheat sheet or quick reference. Templates are available to create objects like databases, tables, views, indexes, stored procedures, triggers, statistics, and functions. Templates are also available for Analysis Services as well. The template scripts contain parameters to help you customize the code. You can Replace Template Parameters dialog box to insert values into the script. An invalid floating point operation occurred If you run any of the above functions they will give you an error related to invalid floating point. Honestly there is no workaround except passing the function appropriate values. SQRT of a negative number will give you result in real numbers which is not supported at this point of time as well LOG of a negative number is not possible (because logarithm is the inverse function of an exponential function and the exponential function is NEVER negative). Validating Spatial Object with IsValidDetailed Function SQL Server 2012 has introduced the new function IsValidDetailed(). This function has made my life very easy. In simple words, this function will check if the spatial object passed is valid or not. If it is valid it will give information that it is valid. If the spatial object is not valid it will return the answer that it is not valid and the reason for the same. This makes it very easy to debug the issue and make the necessary correction. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Faster SQL Server Databases and Applications – Power and Control with SafePeak Caching Options

    - by Pinal Dave
    Update: This blog post is written based on the SafePeak, which is available for free download. Today, I’d like to examine more closely one of my preferred technologies for accelerating SQL Server databases, SafePeak. Safepeak’s software provides a variety of advanced data caching options, techniques and tools to accelerate the performance and scalability of SQL Server databases and applications. I’d like to look more closely at some of these options, as some of these capabilities could help you address lagging database and performance on your systems. To better understand the available options, it is best to start by understanding the difference between the usual “Basic Caching” vs. SafePeak’s “Dynamic Caching”. Basic Caching Basic Caching (or the stale and static cache) is an ability to put the results from a query into cache for a certain period of time. It is based on TTL, or Time-to-live, and is designed to stay in cache no matter what happens to the data. For example, although the actual data can be modified due to DML commands (update/insert/delete), the cache will still hold the same obsolete query data. Meaning that with the Basic Caching is really static / stale cache.  As you can tell, this approach has its limitations. Dynamic Caching Dynamic Caching (or the non-stale cache) is an ability to put the results from a query into cache while maintaining the cache transaction awareness looking for possible data modifications. The modifications can come as a result of: DML commands (update/insert/delete), indirect modifications due to triggers on other tables, executions of stored procedures with internal DML commands complex cases of stored procedures with multiple levels of internal stored procedures logic. When data modification commands arrive, the caching system identifies the related cache items and evicts them from cache immediately. In the dynamic caching option the TTL setting still exists, although its importance is reduced, since the main factor for cache invalidation (or cache eviction) become the actual data updates commands. Now that we have a basic understanding of the differences between “basic” and “dynamic” caching, let’s dive in deeper. SafePeak: A comprehensive and versatile caching platform SafePeak comes with a wide range of caching options. Some of SafePeak’s caching options are automated, while others require manual configuration. Together they provide a complete solution for IT and Data managers to reach excellent performance acceleration and application scalability for  a wide range of business cases and applications. Automated caching of SQL Queries: Fully/semi-automated caching of all “read” SQL queries, containing any types of data, including Blobs, XMLs, Texts as well as all other standard data types. SafePeak automatically analyzes the incoming queries, categorizes them into SQL Patterns, identifying directly and indirectly accessed tables, views, functions and stored procedures; Automated caching of Stored Procedures: Fully or semi-automated caching of all read” stored procedures, including procedures with complex sub-procedure logic as well as procedures with complex dynamic SQL code. All procedures are analyzed in advance by SafePeak’s  Metadata-Learning process, their SQL schemas are parsed – resulting with a full understanding of the underlying code, objects dependencies (tables, views, functions, sub-procedures) enabling automated or semi-automated (manually review and activate by a mouse-click) cache activation, with full understanding of the transaction logic for cache real-time invalidation; Transaction aware cache: Automated cache awareness for SQL transactions (SQL and in-procs); Dynamic SQL Caching: Procedures with dynamic SQL are pre-parsed, enabling easy cache configuration, eliminating SQL Server load for parsing time and delivering high response time value even in most complicated use-cases; Fully Automated Caching: SQL Patterns (including SQL queries and stored procedures) that are categorized by SafePeak as “read and deterministic” are automatically activated for caching; Semi-Automated Caching: SQL Patterns categorized as “Read and Non deterministic” are patterns of SQL queries and stored procedures that contain reference to non-deterministic functions, like getdate(). Such SQL Patterns are reviewed by the SafePeak administrator and in usually most of them are activated manually for caching (point and click activation); Fully Dynamic Caching: Automated detection of all dependent tables in each SQL Pattern, with automated real-time eviction of the relevant cache items in the event of “write” commands (a DML or a stored procedure) to one of relevant tables. A default setting; Semi Dynamic Caching: A manual cache configuration option enabling reducing the sensitivity of specific SQL Patterns to “write” commands to certain tables/views. An optimization technique relevant for cases when the query data is either known to be static (like archive order details), or when the application sensitivity to fresh data is not critical and can be stale for short period of time (gaining better performance and reduced load); Scheduled Cache Eviction: A manual cache configuration option enabling scheduling SQL Pattern cache eviction based on certain time(s) during a day. A very useful optimization technique when (for example) certain SQL Patterns can be cached but are time sensitive. Example: “select customers that today is their birthday”, an SQL with getdate() function, which can and should be cached, but the data stays relevant only until 00:00 (midnight); Parsing Exceptions Management: Stored procedures that were not fully parsed by SafePeak (due to too complex dynamic SQL or unfamiliar syntax), are signed as “Dynamic Objects” with highest transaction safety settings (such as: Full global cache eviction, DDL Check = lock cache and check for schema changes, and more). The SafePeak solution points the user to the Dynamic Objects that are important for cache effectiveness, provides easy configuration interface, allowing you to improve cache hits and reduce cache global evictions. Usually this is the first configuration in a deployment; Overriding Settings of Stored Procedures: Override the settings of stored procedures (or other object types) for cache optimization. For example, in case a stored procedure SP1 has an “insert” into table T1, it will not be allowed to be cached. However, it is possible that T1 is just a “logging or instrumentation” table left by developers. By overriding the settings a user can allow caching of the problematic stored procedure; Advanced Cache Warm-Up: Creating an XML-based list of queries and stored procedure (with lists of parameters) for periodically automated pre-fetching and caching. An advanced tool allowing you to handle more rare but very performance sensitive queries pre-fetch them into cache allowing high performance for users’ data access; Configuration Driven by Deep SQL Analytics: All SQL queries are continuously logged and analyzed, providing users with deep SQL Analytics and Performance Monitoring. Reduce troubleshooting from days to minutes with database objects and SQL Patterns heat-map. The performance driven configuration helps you to focus on the most important settings that bring you the highest performance gains. Use of SafePeak SQL Analytics allows continuous performance monitoring and analysis, easy identification of bottlenecks of both real-time and historical data; Cloud Ready: Available for instant deployment on Amazon Web Services (AWS). As you can see, there are many options to configure SafePeak’s SQL Server database and application acceleration caching technology to best fit a lot of situations. If you’re not familiar with their technology, they offer free-trial software you can download that comes with a free “help session” to help get you started. You can access the free trial here. Also, SafePeak is available to use on Amazon Cloud. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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