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• SQL SERVER – Beginning SQL Server: One Step at a Time – SQL Server Magazine

  - by pinaldave

  I am glad to announce that along with SQLAuthority.com, I will be blogging on the prominent site of SQL Server Magazine. My very first blog post there is already live; read here: Beginning SQL Server: One Step at a Time. My association with SQL Server Magazine has been quite long, I have written nearly 7 to 8 SQL Server articles for the print magazine and it has been a great experience. I used to stay in the United States at that time. I moved back to India for good, and during this process, I had put everything on hold for a while. Just like many things, “temporary” things become “permanent” – coming back to SQLMag was on hold for long time. Well, this New Year, things have changed – once again, I am back with my online presence at SQLMag.com. Everybody is a beginner at every task or activity at some point of his/her life: spelling words for the first time; learning how to drive for the first time, etc. No one is perfect at the start of any task, but every human is different. As time passes, we all develop our interests and begin to study our subject of interest. Most of us dream to get a job in the area of our study – however things change as time passes. I recently read somewhere online (I could not find the link again while writing this one) that all the successful people in various areas have never studied in the area in which they are successful. After going through a formal learning process of what we love, we refuse to stop learning, and we finally stop changing career and focus areas. We move, we dare and we progress. IT field is similar to our life. New IT professionals come to this field every day. There are two types of beginners – a) those who are associated with IT field but not familiar with other technologies, and b) those who are absolutely new to the IT field. Learning a new technology is always exciting and overwhelming for enthusiasts. I am working with database (in particular) for SQL Server for more than 7 years but I am still overwhelmed with so many things to learn. I continue to learn and I do not think that I should ever stop doing so. Just like everybody, I want to be in the race and get ahead in learning the technology. For the same, I am always looking for good guidance. I always try to find a good article, blog or book chapter, which can teach me what I really want to learn at this stage in my career and can be immensely helpful. Quite often, I prefer to read the material where the author does not judge me or assume my understanding. I like to read new concepts like a child, who takes his/her first steps of learning without any prior knowledge. Keeping my personal philosophy and preference in mind, I will be blogging on SQL Server Magazine site. I will be blogging on the beginners stuff. I will be blogging for them, who really want to start and make a mark in this area. I will be blogging for all those who have an extreme passion for learning. I am happy that this is a good start for this year. One of my resolutions is to help every beginner. It is totally possible that in future they all will grow and find the same article quite ‘easy‘ – well when that happens, it indicates the success of the article and material! Well, I encourage everybody to read my SQL Server Magazine blog – I will be blogging there frequently on various topics. To begin, we will be talking about performance tuning, and I assure that I will not shy away from other multiple areas. Read my SQL Server Magazine Blog: Beginning SQL Server: One Step at a Time I think the title says it all. Do leave your comments and feedback to indicate your preference of subject and interest. I am going to continue writing on subject, and the aim is of course to help grow in this field. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority News, T SQL, Technology

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• SQL SERVER – Wait Stats – Wait Types – Wait Queues – Day 0 of 28

  - by pinaldave

  This blog post will have running account of the all the blog post I will be doing in this month related to SQL Server Wait Types and Wait Queues. SQL SERVER – Introduction to Wait Stats and Wait Types – Wait Type – Day 1 of 28 SQL SERVER – Signal Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28 SQL SERVER – DMV – sys.dm_os_wait_stats Explanation – Wait Type – Day 3 of 28 SQL SERVER – DMV – sys.dm_os_waiting_tasks and sys.dm_exec_requests – Wait Type – Day 4 of 28 SQL SERVER – Capturing Wait Types and Wait Stats Information at Interval – Wait Type – Day 5 of 28 SQL SERVER – CXPACKET – Parallelism – Usual Solution – Wait Type – Day 6 of 28 SQL SERVER – CXPACKET – Parallelism – Advanced Solution – Wait Type – Day 7 of 28 SQL SERVER – SOS_SCHEDULER_YIELD – Wait Type – Day 8 of 28 SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28 SQL SERVER – IO_COMPLETION – Wait Type – Day 10 of 28 SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28 SQL SERVER – PAGELATCH_DT, PAGELATCH_EX, PAGELATCH_KP, PAGELATCH_SH, PAGELATCH_UP – Wait Type – Day 12 of 28 SQL SERVER – FT_IFTS_SCHEDULER_IDLE_WAIT – Full Text – Wait Type – Day 13 of 28 SQL SERVER – BACKUPIO, BACKUPBUFFER – Wait Type – Day 14 of 28 SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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• SQL SERVER – Size of Index Table for Each Index – Solution 2

  - by pinaldave

  Earlier I had ran puzzle where I asked question regarding size of index table for each index in database over here SQL SERVER – Size of Index Table – A Puzzle to Find Index Size for Each Index on Table. I had received good amount answers and I had blogged about that here SQL SERVER – Size of Index Table for Each Index – Solution. As a comment to that blog I have received another very interesting comment and that provides near accurate answers to original question. Many thanks to Rama Mathanmohan for providing wonderful solution. SELECT OBJECT_NAME(i.OBJECT_ID) AS TableName, i.name AS IndexName, i.index_id AS IndexID, 8 * SUM(a.used_pages) AS 'Indexsize(KB)' FROM sys.indexes AS i JOIN sys.partitions AS p ON p.OBJECT_ID = i.OBJECT_ID AND p.index_id = i.index_id JOIN sys.allocation_units AS a ON a.container_id = p.partition_id GROUP BY i.OBJECT_ID,i.index_id,i.name ORDER BY OBJECT_NAME(i.OBJECT_ID),i.index_id Let me know if you have any better script for the same. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, Readers Contribution, SQL, SQL Authority, SQL Data Storage, SQL Index, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• SQL SERVER – Get Latest SQL Query for Sessions – DMV

  - by pinaldave

  In recent SQL Training I was asked, how can one figure out what was the last SQL Statement executed in sessions. The query for this is very simple. It uses two DMVs and created following quick script for the same. SELECT session_id, TEXT FROM sys.dm_exec_connections CROSS APPLY sys.dm_exec_sql_text(most_recent_sql_handle) AS ST While working with DMVs if you ever find any DMV has column with name sql_handle you can right away join that DMV with another DMV sys.dm_exec_sql_text and can get the text of the SQL statement. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: DMV, SQL DMV

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• SQL SERVER – Simple Example of Snapshot Isolation – Reduce the Blocking Transactions

  - by pinaldave

  To learn any technology and move to a more advanced level, it is very important to understand the fundamentals of the subject first. Today, we will be talking about something which has been quite introduced a long time ago but not properly explored when it comes to the isolation level. Snapshot Isolation was introduced in SQL Server in 2005. However, the reality is that there are still many software shops which are using the SQL Server 2000, and therefore cannot be able to maintain the Snapshot Isolation. Many software shops have upgraded to the later version of the SQL Server, but their respective developers have not spend enough time to upgrade themselves with the latest technology. “It works!” is a very common answer of many when they are asked about utilizing the new technology, instead of backward compatibility commands. In one of the recent consultation project, I had same experience when developers have “heard about it” but have no idea about snapshot isolation. They were thinking it is the same as Snapshot Replication – which is plain wrong. This is the same demo I am including here which I have created for them. In Snapshot Isolation, the updated row versions for each transaction are maintained in TempDB. Once a transaction has begun, it ignores all the newer rows inserted or updated in the table. Let us examine this example which shows the simple demonstration. This transaction works on optimistic concurrency model. Since reading a certain transaction does not block writing transaction, it also does not block the reading transaction, which reduced the blocking. First, enable database to work with Snapshot Isolation. Additionally, check the existing values in the table from HumanResources.Shift. ALTER DATABASE AdventureWorks SET ALLOW_SNAPSHOT_ISOLATION ON GO SELECT ModifiedDate FROM HumanResources.Shift GO Now, we will need two different sessions to prove this example. First Session: Set Transaction level isolation to snapshot and begin the transaction. Update the column “ModifiedDate” to today’s date. -- Session 1 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN UPDATE HumanResources.Shift SET ModifiedDate = GETDATE() GO Please note that we have not yet been committed to the transaction. Now, open the second session and run the following “SELECT” statement. Then, check the values of the table. Please pay attention on setting the Isolation level for the second one as “Snapshot” at the same time when we already start the transaction using BEGIN TRAN. -- Session 2 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that the values in the table are still original values. They have not been modified yet. Once again, go back to session 1 and begin the transaction. -- Session 1 COMMIT After that, go back to Session 2 and see the values of the table. -- Session 2 SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that the values are yet not changed and they are still the same old values which were there right in the beginning of the session. Now, let us commit the transaction in the session 2. Once committed, run the same SELECT statement once more and see what the result is. -- Session 2 COMMIT SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that it now reflects the new updated value. I hope that this example is clear enough as it would give you good idea how the Snapshot Isolation level works. There is much more to write about an extra level, READ_COMMITTED_SNAPSHOT, which we will be discussing in another post soon. If you wish to use this transaction’s Isolation level in your production database, I would appreciate your comments about their performance on your servers. I have included here the complete script used in this example for your quick reference. ALTER DATABASE AdventureWorks SET ALLOW_SNAPSHOT_ISOLATION ON GO SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 1 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN UPDATE HumanResources.Shift SET ModifiedDate = GETDATE() GO -- Session 2 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 1 COMMIT -- Session 2 SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 2 COMMIT SELECT ModifiedDate FROM HumanResources.Shift GO Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Transaction Isolation

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• SQL SERVER – Simple Example of Snapshot Isolation – Reduce the Blocking Transactions

  - by pinaldave

  To learn any technology and move to a more advanced level, it is very important to understand the fundamentals of the subject first. Today, we will be talking about something which has been quite introduced a long time ago but not properly explored when it comes to the isolation level. Snapshot Isolation was introduced in SQL Server in 2005. However, the reality is that there are still many software shops which are using the SQL Server 2000, and therefore cannot be able to maintain the Snapshot Isolation. Many software shops have upgraded to the later version of the SQL Server, but their respective developers have not spend enough time to upgrade themselves with the latest technology. “It works!” is a very common answer of many when they are asked about utilizing the new technology, instead of backward compatibility commands. In one of the recent consultation project, I had same experience when developers have “heard about it” but have no idea about snapshot isolation. They were thinking it is the same as Snapshot Replication – which is plain wrong. This is the same demo I am including here which I have created for them. In Snapshot Isolation, the updated row versions for each transaction are maintained in TempDB. Once a transaction has begun, it ignores all the newer rows inserted or updated in the table. Let us examine this example which shows the simple demonstration. This transaction works on optimistic concurrency model. Since reading a certain transaction does not block writing transaction, it also does not block the reading transaction, which reduced the blocking. First, enable database to work with Snapshot Isolation. Additionally, check the existing values in the table from HumanResources.Shift. ALTER DATABASE AdventureWorks SET ALLOW_SNAPSHOT_ISOLATION ON GO SELECT ModifiedDate FROM HumanResources.Shift GO Now, we will need two different sessions to prove this example. First Session: Set Transaction level isolation to snapshot and begin the transaction. Update the column “ModifiedDate” to today’s date. -- Session 1 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN UPDATE HumanResources.Shift SET ModifiedDate = GETDATE() GO Please note that we have not yet been committed to the transaction. Now, open the second session and run the following “SELECT” statement. Then, check the values of the table. Please pay attention on setting the Isolation level for the second one as “Snapshot” at the same time when we already start the transaction using BEGIN TRAN. -- Session 2 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that the values in the table are still original values. They have not been modified yet. Once again, go back to session 1 and begin the transaction. -- Session 1 COMMIT After that, go back to Session 2 and see the values of the table. -- Session 2 SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that the values are yet not changed and they are still the same old values which were there right in the beginning of the session. Now, let us commit the transaction in the session 2. Once committed, run the same SELECT statement once more and see what the result is. -- Session 2 COMMIT SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that it now reflects the new updated value. I hope that this example is clear enough as it would give you good idea how the Snapshot Isolation level works. There is much more to write about an extra level, READ_COMMITTED_SNAPSHOT, which we will be discussing in another post soon. If you wish to use this transaction’s Isolation level in your production database, I would appreciate your comments about their performance on your servers. I have included here the complete script used in this example for your quick reference. ALTER DATABASE AdventureWorks SET ALLOW_SNAPSHOT_ISOLATION ON GO SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 1 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN UPDATE HumanResources.Shift SET ModifiedDate = GETDATE() GO -- Session 2 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 1 COMMIT -- Session 2 SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 2 COMMIT SELECT ModifiedDate FROM HumanResources.Shift GO Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Transaction Isolation

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• New Whitepaper: Oracle E-Business Suite on Exadata

  - by Steven Chan

  Our Maximum Availability Architecture (MAA) team has quietly been amassing a formidable set of whitepapers about the Oracle Exadata Database Machine.  They're available here:MAA Best Practices - Exadata Database MachineIf you're one of the lucky ones with access to this hardware platform, you'll be pleased to hear that the MAA team has just published a new whitepaper with best practices for EBS environments:Oracle E-Business Suite on ExadataThis whitepaper covers the following topics:Getting to Exadata -- a high level overview of fresh installation on, and migration to, Exadata Database Machine with pointers to more detailed documentation High Availability and Disaster Recovery -- an overview of our MAA best practices with pointers to our detailed MAA Best Practices documentation Performance and Scalability -- best practices for running Oracle E-Business Suite on Exadata Database Machine based on our internal testing

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• theoretical and practical matrix multiplication FLOP

  - by mjr

  I wrote traditional matrix multiplication in c++ and tried to measure and compare its theoretical and practical FLOP. As I know inner loop of MM has 2 operation therefore simple MM theoretical Flops is 2*n*n*n (2n^3) but in practice I get something like 4n^3 + number of operation which is 2 i.e. 6n^3 also if I just try to add up only one array a[i][j]++ practical flops then calculate like 3n^3 and not n^3 as you see again it is 2n^3 +1 operation and not 1 operation * n^3 . This is in case if I use 1D array in three nested loops as Matrix multiplication and compare flop, practical flop is the same (near) the theoretical flop and depend exactly as the number of operation in inner loop.I could not find the reason for this behaviour. what is the reason in both case? I know that theoretical flop is not the same as practical one because of some operations like load etc. system specification: Intel core2duo E4500 3700g memory L2 cache 2M x64 fedora 17 sample results: Matrix matrix multiplication 512*512 Real_time: 1.718368 Proc_time: 1.227672 Total flpops: 807,107,072 MFLOPS: 657.429016 Real_time: 3.608078 Proc_time: 3.042272 Total flpops: 807,024,448 MFLOPS: 265.270355 theoretical flop: 2*512*512*512=268,435,456 Practical flops= 6*512^3 =807,107,072 Using 1 dimensional array float d[size][size]:512 or any size for (int j = 0; j < size; ++j) { for (int k = 0; k < size; ++k) { d[k]=d[k]+e[k]+f[k]+g[k]+r; } } Real_time: 0.002288 Proc_time: 0.002260 Total flpops: 1,048,578 MFLOPS: 464.027161 theroretical flop: *4n^2=4*512^2=1,048,576* practical flop : 4n^2+overhead (other operation?)=1,048,578 3 loop version: Real_time: 1.282257 Proc_time: 1.155990 Total flpops: 536,872,000 MFLOPS: 464.426117 theoretical flop:4n^3 = 536,870,912 practical flop: *4n^3=4*512^3+overheads(other operation?)=536,872,000* thank you

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• Strategy to find bottleneck in a network

  - by Simone

  Our enterprise is having some problem when the number of incoming request goes beyond a certain amount. To make things simpler, we have N websites that uses, amongst other, a local web service. This service is hosted by IIS, and it's a .NET 4.0 (C#) application executed in a farm. It's REST-oriented, built around OpenRasta. As already mentioned, by stress testing it with JMeter, we've found that beyond a certain amount of request the service's performance drop. Anyway, this service is, amongst other, a client itself of other 3 distinct web services and also a client for a DB server, so it's not very clear what really is the culprit of this abrupt decay. In turn, these 3 other web services are installed in our farm too, and client of other DB servers (and services, possibly, that are out of my team control). What strategy do you suggest to try to locate where the bottleneck(s) are? Do you have any high-level suggestions?

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• optimizing an sql query using inner join and order by

  - by Sergio B

  I'm trying to optimize the following query without success. Any idea where it could be indexed to prevent the temporary table and the filesort? EXPLAIN SELECT SQL_NO_CACHE `groups`.* FROM `groups` INNER JOIN `memberships` ON `groups`.id = `memberships`.group_id WHERE ((`memberships`.user_id = 1) AND (`memberships`.`status_code` = 1 AND `memberships`.`manager` = 0)) ORDER BY groups.created_at DESC LIMIT 5;` +----+-------------+-------------+--------+--------------------------+---------+---------+---------------------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------------+--------+--------------------------+---------+---------+---------------------------------------------+------+----------------------------------------------+ | 1 | SIMPLE | memberships | ref | grp_usr,grp,usr,grp_mngr | usr | 5 | const | 5 | Using where; Using temporary; Using filesort | | 1 | SIMPLE | groups | eq_ref | PRIMARY | PRIMARY | 4 | sportspool_development.memberships.group_id | 1 | | +----+-------------+-------------+--------+--------------------------+---------+---------+---------------------------------------------+------+----------------------------------------------+ 2 rows in set (0.00 sec) +--------+------------+-----------------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | +--------+------------+-----------------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+ | groups | 0 | PRIMARY | 1 | id | A | 6 | NULL | NULL | | BTREE | | | groups | 1 | index_groups_on_name | 1 | name | A | 6 | NULL | NULL | YES | BTREE | | | groups | 1 | index_groups_on_privacy_setting | 1 | privacy_setting | A | 6 | NULL | NULL | YES | BTREE | | | groups | 1 | index_groups_on_created_at | 1 | created_at | A | 6 | NULL | NULL | YES | BTREE | | | groups | 1 | index_groups_on_id_and_created_at | 1 | id | A | 6 | NULL | NULL | | BTREE | | | groups | 1 | index_groups_on_id_and_created_at | 2 | created_at | A | 6 | NULL | NULL | YES | BTREE | | +--------+------------+-----------------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+ +-------------+------------+----------------------------------------------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | +-------------+------------+----------------------------------------------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+ | memberships | 0 | PRIMARY | 1 | id | A | 2 | NULL | NULL | | BTREE | | | memberships | 0 | grp_usr | 1 | group_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 0 | grp_usr | 2 | user_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | grp | 1 | group_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | usr | 1 | user_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | grp_mngr | 1 | group_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | grp_mngr | 2 | manager | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | complex_index | 1 | group_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | complex_index | 2 | user_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | complex_index | 3 | status_code | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | complex_index | 4 | manager | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | index_memberships_on_user_id_and_status_code_and_manager | 1 | user_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | index_memberships_on_user_id_and_status_code_and_manager | 2 | status_code | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | index_memberships_on_user_id_and_status_code_and_manager | 3 | manager | A | 2 | NULL | NULL | YES | BTREE | | +-------------+------------+----------------------------------------------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+

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• Should I group all of my .js files into one large bundle?

  - by Scottie

  One of the difficulties I'm running into with my current project is that the previous developer spaghetti'd the javascript code in lots of different files. We have modal dialogs that are reused in different places and I find that the same .js file is often loaded twice. My thinking is that I'd like to just load all of the .js files in _Layout.cshtml, and that way I know it's loaded once and only once. Also, the client should only have to download this file once as well. It should be cached and therefore shouldn't really be a performance hit, except for the first page load. I should probably note that I am using ASP.Net bundling as well and loading most of the jQuery/bootstrap/etc from CDN's. Is there anything else that I'm not thinking of that would cause problems here? Should I bundle everything into a single file?

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• how to write this typical mysql query( ho to use subquery column into main query)

  - by I Like PHP

  I HAVE TWO TABLES shown below table_joining id join_id(PK) transfer_id(FK) unit_id transfer_date joining_date 1 j_1 t_1 u_1 2010-06-05 2010-03-05 2 j_2 t_2 u_3 2010-05-10 2010-03-10 3 j_3 t_3 u_6 2010-04-10 2010-01-01 4 j_5 NULL u_3 NULL 2010-06-05 5 j_6 NULL u_4 NULL 2010-05-05 table_transfer id transfer_id(PK) pastUnitId futureUnitId effective_transfer_date 1 t_1 u_3 u_1 2010-06-05 2 t_2 u_6 u_1 2010-05-10 3 t_3 u_5 u_3 2010-04-10 now i want to know total employee detalis( using join_id) which are currently working on unit u_3 . means i want only join_id j_1 (has transfered but effective_transfer_date is future date, right now in u_3) j_2 ( tansfered and right now in `u_3` bcoz effective_transfer_date has been passed) j_6 ( right now in `u_3` and never transfered) what i need to take care of below steps( as far as i know ) <1> first need to check from table_joining whether transfer_id is NULL or not <2> if transfer_id= is NULL then see unit_id=u_3 where joining_date <=CURDATE() ( means that person already joined u_3) <3> if transfer_id is NOT NULL then go to table_transfer using transfer_id (foreign key reference) <4> now see the effective_transfer_date regrading that transfer_id whether effective_transfer_date<=CURDATE() <5> if transfer date has been passed(means transfer has been done) then return futureUnitID otherwise return pastUnitID i used two separate query but don't know how to join those query?? for step <1 ans <2 SELECT unit_id FROM table_joining WHERE joining_date<=CURDATE() AND transfer_id IS NULL AND unit_id='u_3' for step<5 SELECT IF(effective_transfer_date <= CURDATE(),futureUnitId,pastUnitId) AS currentUnitID FROM table_transfer // here how do we select only those rows which have currentUnitID='u_3' ?? please guide me the process?? i m just confused with JOINS. i think using LEFT JOIN can return the data i need, but i m not getting how to implement ...please help me. Thanks for helping me alwayz

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• Is there a PHP benchmark that meets these specific criteria? [closed]

  - by Alex R

  I'm working on a tool which converts PHP code to Scala. As one of the finishing touches, I'm in need of a really good (er, somewhat biased) benchmark. By dumb luck my first benchmark attempt was with some code which uses bcmath extensively, which unfortunately is 1000x slower in Java, making the Scala code 22x slower overall than the original PHP. So I'm looking for some meaningful PHP benchmark with the following characteristics: The PHP source needs to be in a single file. It should solve a real-world problem. No silly looping over empty methods etc. I need it to be simple to setup - no databases, hard-to-find input files, etc. Simple text input and output preferred. It should not use features that are slow in Java (BigInteger, trigonometric functions, etc). It should not use exoteric or dynamic PHP functions (e.g. no "eval" or "variable vars"). It should not over-rely on built-in libraries, e.g. MD5, crypt, etc. It should not be I/O bound. A CPU-bound memory-hungry algorithm is preferred. Basically, intensive OO operations, integer and string manipulation, recursion, etc would be great. Thanks

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• What's the largest (most complex) PHP algorithm ever implemented in a single monolithic PHP script?

  - by Alex R

  I'm working on a tool which converts PHP code to Scala. As one of the finishing touches, I'm in need of a really good (er, somewhat biased) benchmark. By dumb luck my first benchmark attempt was with some code which uses bcmath extensively, which unfortunately is 1000x slower in Java, making the Scala code 22x slower overall than the original PHP. So I'm looking for some meaningful PHP benchmark with the following characteristics: The source needs to be in a single file. I need it to be simple to setup - no databases, hard-to-find input files, etc. Simple text input and output preferred. It should not use features that are slow in Java (BigInteger, trigonometric functions, etc). It should not use exoteric or dynamic PHP functions (e.g. no "eval" or "variable vars"). It should not over-rely on built-in libraries, e.g. MD5, crypt, etc. It should not be I/O bound. A CPU-bound memory-hungry algorithm is preferred. Basically, intensive OO operations, integer and string manipulation, recursion, etc would be great. Thanks

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• Designing complex query builders in java/jpa/hibernate

  - by Ramraj Edagutti

  I need to build complex sql queries programatically, based on large filter conditions. For example, below are few sample/hypothitical filter conditions, based on which i need to fetch users Country: india States: Andhra Pradesh(AP), Gujarat(GUJ), karnataka(KTK) Districts: All districts in AP except 3 district, 5 any districts from GUJ, all district from KTK except 1 district Cities: All cities in AP, all cities except few, include only 50 specific cities from KTK Villages: similar conditions like above with varies combinations... Currently, we have a query builder, which is very complex in nature, and not easy to modify/re-factory for improvements. So, thinking of complete re-design of it. Any suggesations on how to build this kind of complex query builders programmatically using some best practices/deisgn patterns?

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• Power Query in Modern Corporate BI–Copenhagen, June 3, 2014–#powerquery

  - by Marco Russo (SQLBI)

  I will be in Copenhagen to deliver the SSAS Tabular Workshop on June 2-4, 2014 (few seats still available, but hurry up!). In the same week I will be a speaker in an evening community event, MsBIP møde nr. 21, delivering the Power Query in Modern Corporate BI session that I also presented at TechEd North America 2014 last week. It’s not just a session about Power Query, there is a broader scope related to Corporate BI vs. Self-Service BI, which could be open to many consideration. I think that the two worlds can (and should) collaborate, instead of fighting against each other, especially when there is an existing investment in Corporate BI. I hope to meet many of you there!

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• How to programmatically construct textual query

  - by stibi

  Here is a query language, more specifically, it's JQL, you can use it in Jira, to search for issues, it's something like SQL, but quite simpler. My case is that, I need to construct such queries programmatically, in my application. Something like: JQLMachine jqlMachine = new JQLMachine() jqlMachine.setStatuses("Open", "In Progress") jqlMachine.setReporter("foouser", "baruser") jqlMachine.setDateRange(...) jqlMachine.getQuery() --> String with corresponding JQL query is returned You get my point I hope. I can imagine the code for this, but it's not nice, using my current knowledge how I'd do that. That's why I'm asking. What you'd advice to use to create such thing. I believe some patterns for creating something like this already exist and there is already best practices, how to do that in good way.

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• $query returns results but not the ones i want: $query looks good to me :S

  - by Toni Michel Caubet

  I'll start again, Lets say My data is: Table element (id,name,....) 1, name element 1, .... 2, name element 2, .... 3, name element 3, .... Table tags (id,name,id_element, ....) 1, happy , 1 2, result, 1 3, very , 1 4, element, 2 5, another, 3 6, element, 1 7, happy, 2 So if search is 'very, happy,element,result': Results i would like 1) element with id = 2 because it has all tags 2) element with id = 1 because it has the tag 'element' and the tag 'happy' (only 2 less taggs) 3) .... (only 3 less taggs) So if search is 'happy,element': Results i would like 1) element with id = 1 because it has all tags (and no more) 2) element with id = 2 because it has the tag 'element' and the tag 'happy' (and two more tags) 3) .... and 3 more tags This is an echo to my query: (it doesn't fit al requirements i wrote, but its first test to find with matched tags) SELECT element.id as id_deseada,tagg.* FROM element,tagg WHERE tagg.id_element = element.id AND tagg.nombre IN ('happy','tagg','result') GROUP BY tagg.id_element ORDER BY element.votos This returns 10 duplicated elements... :S and doen't even have all taggs (and on database there are taggs with 'happy' results) if it helps, thats how i get the elements of a tag (by name and with only one tagg) $query = "SELECT element.id FROM element,tagg WHERE tagg.nombre = '$nombre_tagg' AND tagg.id_element = element.id AND lan = '$lan' GROUP BY tagg.id_element"; I hope it's a bit easier to understand now, excuse my english.. :) Thanks a lot for you possible aportation!

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• FreeBSD performance tuning. Sysctls, loader.conf, kernel.

  - by SaveTheRbtz

  I wanted to share knowledge of tuning FreeBSD via sysctls, so i'm posting them with comments. Based on Igor Sysoev (author of nginx) presentation about FreeBSD tuning up to 100,000-200,000 active connections. Sysctls are for 7.x FreeBSD. Since 7.2 amd64 some of them are tuned well by default. Prior 7.0 some of them are boot only (set via /boot/loader.conf) or does not exist at all. Highload web server sysctls: # Max. backlog size kern.ipc.somaxconn=4096 # Shared memory // 7.2+ can use shared memory > 2Gb kern.ipc.shmmax=2147483648 # Sockets kern.ipc.maxsockets=204800 # Do not use lager sockbufs on 8.0 # ( http://old.nabble.com/Significant-performance-regression-for-increased-maxsockbuf-on-8.0-RELEASE-tt26745981.html#a26745981 ) kern.ipc.maxsockbuf=262144 # Recive clusters (on amd64 7.2+ 65k is default) # For such high value vm.kmem_size must be increased to 3G #kern.ipc.nmbclusters=229376 # Jumbo pagesize(4k/8k) clusters # Used as general packet storage for jumbo frames # can be monitored via `netstat -m` #kern.ipc.nmbjumbop=192000 # Jumbo 9k/16k clusters # If you are using them #kern.ipc.nmbjumbo9=24000 #kern.ipc.nmbjumbo16=10240 # Every socket is a file, so increase them kern.maxfiles=204800 kern.maxfilesperproc=200000 kern.maxvnodes=200000 # Turn off receive autotuning #net.inet.tcp.recvbuf_auto=0 # Small receive space, only usable on http-server, on file server this # should be increased to 65535 or even more #net.inet.tcp.recvspace=8192 # Small send space is useful for http servers that serve small files # Autotuned since 7.x net.inet.tcp.sendspace=16384 # This should be enabled if you going to use big spaces (>64k) #net.inet.tcp.rfc1323=1 # Turn this off on highspeed, lossless connections (LAN 1Gbit+) #net.inet.tcp.delayed_ack=0 # This feature is useful if you are serving data over modems, Gigabit Ethernet, # or even high speed WAN links (or any other link with a high bandwidth delay product), # especially if you are also using window scaling or have configured a large send window. # You can try setting it to 0 on fileserver with 1GBit+ interfaces # Automatically disables on small RTT ( http://www.freebsd.org/cgi/cvsweb.cgi/src/sys/netinet/tcp_subr.c?#rev1.237 ) #net.inet.tcp.inflight.enable=0 # Disable randomizing of ports to avoid false RST # Before usage check SA here www.bsdcan.org/2006/papers/ImprovingTCPIP.pdf # (it's also says that port randomization auto-disables at some conn.rates, but I didn't tested it thou) #net.inet.ip.portrange.randomized=0 # Increase portrange # For outgoing connections only. Good for seed-boxes and ftp servers. net.inet.ip.portrange.first=1024 net.inet.ip.portrange.last=65535 # Security net.inet.ip.redirect=0 net.inet.ip.sourceroute=0 net.inet.ip.accept_sourceroute=0 net.inet.icmp.maskrepl=0 net.inet.icmp.log_redirect=0 net.inet.icmp.drop_redirect=1 net.inet.tcp.drop_synfin=1 # Security net.inet.udp.blackhole=1 net.inet.tcp.blackhole=2 # Increases default TTL, sometimes useful # Default is 64 net.inet.ip.ttl=128 # Lessen max segment life to conserve resources # ACK waiting time in miliseconds (default: 30000 from RFC) net.inet.tcp.msl=5000 # Max bumber of timewait sockets net.inet.tcp.maxtcptw=40960 # Don't use tw on local connections # As of 15 Apr 2009. Igor Sysoev says that nolocaltimewait has some buggy realization. # So disable it or now till get fixed #net.inet.tcp.nolocaltimewait=1 # FIN_WAIT_2 state fast recycle net.inet.tcp.fast_finwait2_recycle=1 # Time before tcp keepalive probe is sent # default is 2 hours (7200000) #net.inet.tcp.keepidle=60000 # Should be increased until net.inet.ip.intr_queue_drops is zero net.inet.ip.intr_queue_maxlen=4096 # Interrupt handling via multiple CPU, but with context switch. # You can play with it. Default is 1; #net.isr.direct=0 # This is for routers only #net.inet.ip.forwarding=1 #net.inet.ip.fastforwarding=1 # This speed ups dummynet when channel isn't saturated net.inet.ip.dummynet.io_fast=1 # Increase dummynet(4) hash #net.inet.ip.dummynet.hash_size=2048 #net.inet.ip.dummynet.max_chain_len # Should be increased when you have A LOT of files on server # (Increase until vfs.ufs.dirhash_mem becames lower) vfs.ufs.dirhash_maxmem=67108864 # Explicit Congestion Notification (see http://en.wikipedia.org/wiki/Explicit_Congestion_Notification) net.inet.tcp.ecn.enable=1 # Flowtable - flow caching mechanism # Useful for routers #net.inet.flowtable.enable=1 #net.inet.flowtable.nmbflows=65535 # Extreme polling tuning #kern.polling.burst_max=1000 #kern.polling.each_burst=1000 #kern.polling.reg_frac=100 #kern.polling.user_frac=1 #kern.polling.idle_poll=0 # IPFW dynamic rules and timeouts tuning # Increase dyn_buckets till net.inet.ip.fw.curr_dyn_buckets is lower net.inet.ip.fw.dyn_buckets=65536 net.inet.ip.fw.dyn_max=65536 net.inet.ip.fw.dyn_ack_lifetime=120 net.inet.ip.fw.dyn_syn_lifetime=10 net.inet.ip.fw.dyn_fin_lifetime=2 net.inet.ip.fw.dyn_short_lifetime=10 # Make packets pass firewall only once when using dummynet # i.e. packets going thru pipe are passing out from firewall with accept #net.inet.ip.fw.one_pass=1 # shm_use_phys Wires all shared pages, making them unswappable # Use this to lessen Virtual Memory Manager's work when using Shared Mem. # Useful for databases #kern.ipc.shm_use_phys=1 /boot/loader.conf: # Accept filters for data, http and DNS requests # Usefull when your software uses select() instead of kevent/kqueue or when you under DDoS # DNS accf available on 8.0+ accf_data_load="YES" accf_http_load="YES" accf_dns_load="YES" # Async IO system calls aio_load="YES" # Adds NCQ support in FreeBSD # WARNING! all ad[0-9]+ devices will be renamed to ada[0-9]+ # 8.0+ only #ahci_load= #siis_load= # Increase kernel memory size to 3G. # # Use ONLY if you have KVA_PAGES in kernel configuration, and you have more than 3G RAM # Otherwise panic will happen on next reboot! # # It's required for high buffer sizes: kern.ipc.nmbjumbop, kern.ipc.nmbclusters, etc # Useful on highload stateful firewalls, proxies or ZFS fileservers # (FreeBSD 7.2+ amd64 users: Check that current value is lower!) #vm.kmem_size="3G" # Older versions of FreeBSD can't tune maxfiles on the fly #kern.maxfiles="200000" # Useful for databases # Sets maximum data size to 1G # (FreeBSD 7.2+ amd64 users: Check that current value is lower!) #kern.maxdsiz="1G" # Maximum buffer size(vfs.maxbufspace) # You can check current one via vfs.bufspace # Should be lowered/upped depending on server's load-type # Usually decreased to preserve kmem # (default is 200M) #kern.maxbcache="512M" # Sendfile buffers # For i386 only #kern.ipc.nsfbufs=10240 # syncache Hash table tuning net.inet.tcp.syncache.hashsize=1024 net.inet.tcp.syncache.bucketlimit=100 # Incresed hostcache net.inet.tcp.hostcache.hashsize="16384" net.inet.tcp.hostcache.bucketlimit="100" # TCP control-block Hash table tuning net.inet.tcp.tcbhashsize=4096 # Enable superpages, for 7.2+ only # Also read http://lists.freebsd.org/pipermail/freebsd-hackers/2009-November/030094.html vm.pmap.pg_ps_enabled=1 # Usefull if you are using Intel-Gigabit NIC #hw.em.rxd=4096 #hw.em.txd=4096 #hw.em.rx_process_limit="-1" # Also if you have ALOT interrupts on NIC - play with following parameters # NOTE: You should set them for every NIC #dev.em.0.rx_int_delay: 250 #dev.em.0.tx_int_delay: 250 #dev.em.0.rx_abs_int_delay: 250 #dev.em.0.tx_abs_int_delay: 250 # There is also multithreaded version of em drivers can be found here: # http://people.yandex-team.ru/~wawa/ # # for additional em monitoring and statistics use # `sysctl dev.em.0.stats=1 ; dmesg` # #Same tunings for igb #hw.igb.rxd=4096 #hw.igb.txd=4096 #hw.igb.rx_process_limit=100 # Some useful netisr tunables. See sysctl net.isr #net.isr.defaultqlimit=4096 #net.isr.maxqlimit: 10240 # Bind netisr threads to CPUs #net.isr.bindthreads=1 # Nicer boot logo =) loader_logo="beastie" And finally here is my additions to GENERIC kernel # Just some of them, see also # cat /sys/{i386,amd64,}/conf/NOTES # This one useful only on i386 #options KVA_PAGES=512 # You can play with HZ in environments with high interrupt rate (default is 1000) # 100 is for my notebook to prolong it's battery life #options HZ=100 # Polling is goot on network loads with high packet rates and low-end NICs # NB! Do not enable it if you want more than one netisr thread #options DEVICE_POLLING # Eliminate datacopy on socket read-write # To take advantage with zero copy sockets you should have an MTU of 8K(amd64) # (4k for i386). This req. is only for receiving data. # Read more in man zero_copy_sockets #options ZERO_COPY_SOCKETS # Support TCP sign. Used for IPSec options TCP_SIGNATURE options IPSEC # This ones can be loaded as modules. They described in loader.conf section #options ACCEPT_FILTER_DATA #options ACCEPT_FILTER_HTTP # Adding ipfw, also can be loaded as modules options IPFIREWALL options IPFIREWALL_VERBOSE options IPFIREWALL_VERBOSE_LIMIT=10 options IPFIREWALL_DEFAULT_TO_ACCEPT options IPFIREWALL_FORWARD # Adding kernel NAT options IPFIREWALL_NAT options LIBALIAS # Traffic shaping options DUMMYNET # Divert, i.e. for userspace NAT options IPDIVERT # This is for OpenBSD's pf firewall device pf device pflog # pf's QoS - ALTQ options ALTQ options ALTQ_CBQ # Class Bases Queuing (CBQ) options ALTQ_RED # Random Early Detection (RED) options ALTQ_RIO # RED In/Out options ALTQ_HFSC # Hierarchical Packet Scheduler (HFSC) options ALTQ_PRIQ # Priority Queuing (PRIQ) options ALTQ_NOPCC # Required for SMP build # Pretty console # Manual can be found here http://forums.freebsd.org/showthread.php?t=6134 #options VESA #options SC_PIXEL_MODE # Disable reboot on Ctrl Alt Del #options SC_DISABLE_REBOOT # Change normal|kernel messages color options SC_NORM_ATTR=(FG_GREEN|BG_BLACK) options SC_KERNEL_CONS_ATTR=(FG_YELLOW|BG_BLACK) # More scroll space options SC_HISTORY_SIZE=8192 # Adding hardware crypto device device crypto device cryptodev # Useful network interfaces device vlan device tap #Virtual Ethernet driver device gre #IP over IP tunneling device if_bridge #Bridge interface device pfsync #synchronization interface for PF device carp #Common Address Redundancy Protocol device enc #IPsec interface device lagg #Link aggregation interface device stf #IPv4-IPv6 port # Also for my notebook, but may be used with Opteron #device amdtemp # Support for ECMP. More than one route for destination # Works even with default route so one can use it as LB for two ISP # For now code is unstable and panics (panic: rtfree 2) on route deletions. #options RADIX_MPATH # Multicast routing #options MROUTING #options PIM # DTrace options KDTRACE_HOOKS # all architectures - enable general DTrace hooks options DDB_CTF # all architectures - kernel ELF linker loads CTF data #options KDTRACE_FRAME # amd64-only # Adaptive spining in lockmgr (8.x+) # See http://www.mail-archive.com/[email protected]/msg10782.html options ADAPTIVE_LOCKMGRS # UTF-8 in console (9.x+) #options TEKEN_UTF8 #options TEKEN_XTERM # NCQ support # WARNING! all ad[0-9]+ devices will be renamed to ada[0-9]+ #options ATA_CAM # FreeBSD 9+ # Deadlock resolver thread # For additional information see http://www.mail-archive.com/[email protected]/msg18124.html #options DEADLKRES PS. Also most of FreeBSD's limits can be monitored by # vmstat -z and # limits PPS. variety of network counters can be monitored via # netstat -s In FreeBSD-9 netstat's -Q option appeared, try following command to display netisr stats # netstat -Q PPPS. also see # man 7 tuning PPPPS. I wanted to thank FreeBSD community, especially author of nginx - Igor Sysoev, nginx-ru@ and FreeBSD-performance@ mailing lists for providing useful information about FreeBSD tuning. So here is the question: What tunings are you using on yours FreeBSD servers? You can also post your /etc/sysctl.conf, /boot/loader.conf, kernel options, etc with description of its' meaning (do not copy-paste from sysctl -d). Don't forget to specify server type (web, smb, gateway, etc) Let's share experience!

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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 Intersection Conference, Las Vegas MGM Grand 10-13 November 2014

  - by Paul White

  I am very pleased to announce that I will be speaking at the SQL Intersection conference in Las Vegas again this year. This time around, I am giving a full-day workshop, "Mastering SQL Server Execution Plan Analysis" as well as a two-part session, "Parallel Query Execution" during the main conference. The workshop is a pre-conference event, held on Sunday 9 November (straight after this year's PASS Summit). Being on Sunday gives you the whole Monday off to recover and before the...(read more)

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• sort mysql query by filtered query

  - by kalpaitch

  I have two mysql queries: $sql = "SELECT * FROM content WHERE threadName LIKE '%$filter%' ORDER BY lastUpdated desc"; and $sql = "SELECT * FROM content ORDER BY lastUpdated desc"; The end result is to have all rows returned from a particular table 'content' but have those that match the variable $filter at the top. Is there either a single query that could combine these two or should I be using a JOIN?

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• How to apply GROUP_CONCAT in mysql Query

  - by Query Master

  How to apply GROUP_CONCAT in this Query if you guys have any idea or any alternate solution about this please share me. Helps are definitely appreciated also (see Query or result required) Query SELECT WEEK(cpd.added_date) AS week_no,COUNT(cpd.result) AS death_count FROM cron_players_data cpd WHERE cpd.player_id = 81 AND cpd.result = 2 AND cpd.status = 1 GROUP BY WEEK(cpd.added_date); Query output result screen Result Required 23,24,25 AS week_no 2,3,1 AS death_count

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• Why VM snapshots are affecting performance?

  - by Samselvaprabu

  I read in one of the VMware KB article says that snapshots will directly proportional to VM performance. But my team keep asking me how snapshots can affect performance. I would like to give them solid reason behind the statement that snapshots are performance killers. Can any one explain a little bit theory behind why actually snapshots are affecting the performance? Is it just because Disk I/O rate of hard disk would be slow?

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• SQL SERVER – Fastest Way to Restore the Database

  - by pinaldave

  A few days ago, I received following email: “Pinal, We are in an emergency situation. We have a large database of around 80+ GB and its backup is of 50+ GB in size. We need to restore this database ASAP and use it; however, restoring the database takes forever. Do you think a compressed backup would solve our problem? Any other ideas you got?” First of all, the asker has already answered his own question. Yes; I have seen that if you are using a compressed backup, it takes lesser time when you try to restore a database. I have previously blogged about the same subject. Here are the links to those blog posts: SQL SERVER – Data and Page Compressions – Data Storage and IO Improvement SQL SERVER – 2008 – Introduction to Row Compression SQL SERVER – 2008 – Introduction to New Feature of Backup Compression However, if your database is very large that it still takes a few minutes to restore the database even though you use any of the features listed above, then it will really take some time to restore the database. If there is urgency and there is no time you can spare for restoring the database, then you can use the wonderful tool developed by Idera called virtual database. This tool restores a certain database in just a few seconds so it will readily be available for usage. I have in depth written my experience with this tool in the article here SQL SERVER – Retrieve and Explore Database Backup without Restoring Database – Idera virtual database. Let me know your experience in this scenario. Have you ever needed your database backup restored very quickly, what did you do in that scenario. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, Readers Question, SQL, SQL Authority, SQL Backup and Restore, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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