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• SQL SERVER – Single Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28

  - by pinaldave

  In this post, let’s delve a bit more in depth regarding wait stats. The very first question: when do the wait stats occur? Here is the simple answer. When SQL Server is executing any task, and if for any reason it has to wait for resources to execute the task, this wait is recorded by SQL Server with the reason for the delay. Later on we can analyze these wait stats to understand the reason the task was delayed and maybe we can eliminate the wait for SQL Server. It is not always possible to remove the wait type 100%, but there are few suggestions that can help. Before we continue learning about wait types and wait stats, we need to understand three important milestones of the query life-cycle. Running - a query which is being executed on a CPU is called a running query. This query is responsible for CPU time. Runnable – a query which is ready to execute and waiting for its turn to run is called a runnable query. This query is responsible for Single Wait time. (In other words, the query is ready to run but CPU is servicing another query). Suspended – a query which is waiting due to any reason (to know the reason, we are learning wait stats) to be converted to runnable is suspended query. This query is responsible for wait time. (In other words, this is the time we are trying to reduce). In simple words, query execution time is a summation of the query Executing CPU Time (Running) + Query Wait Time (Suspended) + Query Single Wait Time (Runnable). Again, it may be possible a query goes to all these stats multiple times. Let us try to understand the whole thing with a simple analogy of a taxi and a passenger. Two friends, Tom and Danny, go to the mall together. When they leave the mall, they decide to take a taxi. Tom and Danny both stand in the line waiting for their turn to get into the taxi. This is the Signal Wait Time as they are ready to get into the taxi but the taxis are currently serving other customer and they have to wait for their turn. In other word they are in a runnable state. Now when it is their turn to get into the taxi, the taxi driver informs them he does not take credit cards and only cash is accepted. Neither Tom nor Danny have enough cash, they both cannot get into the vehicle. Tom waits outside in the queue and Danny goes to ATM to fetch the cash. During this time the taxi cannot wait, they have to let other passengers get into the taxi. As Tom and Danny both are outside in the queue, this is the Query Wait Time and they are in the suspended state. They cannot do anything till they get the cash. Once Danny gets the cash, they are both standing in the line again, creating one more Single Wait Time. This time when their turn comes they can pay the taxi driver in cash and reach their destination. The time taken for the taxi to get from the mall to the destination is running time (CPU time) and the taxi is running. I hope this analogy is bit clear with the wait stats. You can check the single wait stats using following query of Glenn Berry. -- Signal Waits for instance SELECT CAST(100.0 * SUM(signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%signal (cpu) waits], CAST(100.0 * SUM(wait_time_ms - signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%resource waits] FROM sys.dm_os_wait_stats OPTION (RECOMPILE); Higher the single wait stats are not good for the system. Very high value indicates CPU pressure. In my experience, when systems are running smooth and without any glitch the single wait stat is lower than 20%. Again, this number can be debated (and it is from my experience and is not documented anywhere). In other words, lower is better and higher is not good for the system. In future articles we will discuss in detail the various wait types and wait stats and their resolution. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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• Query returns too few rows

  - by Tareq

  setup: mysql> create table product_stock( product_id integer, qty integer, branch_id integer); Query OK, 0 rows affected (0.17 sec) mysql> create table product( product_id integer, product_name varchar(255)); Query OK, 0 rows affected (0.11 sec) mysql> insert into product(product_id, product_name) values(1, 'Apsana White DX Pencil'); Query OK, 1 row affected (0.05 sec) mysql> insert into product(product_id, product_name) values(2, 'Diamond Glass Marking Pencil'); Query OK, 1 row affected (0.03 sec) mysql> insert into product(product_id, product_name) values(3, 'Apsana Black Pencil'); Query OK, 1 row affected (0.03 sec) mysql> insert into product_stock(product_id, qty, branch_id) values(1, 100, 1); Query OK, 1 row affected (0.03 sec) mysql> insert into product_stock(product_id, qty, branch_id) values(1, 50, 2); Query OK, 1 row affected (0.03 sec) mysql> insert into product_stock(product_id, qty, branch_id) values(2, 80, 1); Query OK, 1 row affected (0.03 sec) my query: mysql> SELECT IFNULL(SUM(s.qty),0) AS stock, product_name FROM product_stock s RIGHT JOIN product p ON s.product_id=p.product_id WHERE branch_id=1 GROUP BY product_name ORDER BY product_name; returns: +-------+-------------------------------+ | stock | product_name | +-------+-------------------------------+ | 100 | Apsana White DX Pencil | | 80 | Diamond Glass Marking Pencil | +-------+-------------------------------+ 1 row in set (0.00 sec) But I want to have the following result: +-------+------------------------------+ | stock | product_name | +-------+------------------------------+ | 0 | Apsana Black Pencil | | 100 | Apsana White DX Pencil | | 80 | Diamond Glass Marking Pencil | +-------+------------------------------+ To get this result what mysql query should I run?

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• How do I filter one of the columns in a SQL Server SQL Query

  - by Kent S. Clarkson

  I have a table (that relates to a number of other tables) where I would like to filter ONE of the columns (RequesterID) - that column will be a combobox where only people that are not sales people should be selectable. Here is the "unfiltered" query, lets call it QUERY 1: SELECT RequestsID, RequesterID, ProductsID FROM dbo.Requests If using a separate query, lets call it QUERY 2, to filter RequesterID (which is a People related column, connected to People.PeopleID), it would look like this: SELECT People.PeopleID FROM People INNER JOIN Roles ON People.RolesID = Roles.RolesID INNER JOIN Requests ON People.PeopleID = Requests.RequesterID WHERE (Roles.Role <> N'SalesGuy') ORDER BY Requests.RequestsID Now, is there a way of "merging" the QUERY 2 into QUERY 1? (dbo.Requests in QUERY 1 has RequesterID populated as a Foreign Key from dbo.People, so no problem there... The connections are all right, just not know how to write the SQL query!)

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• MySQL slow query log logging all queries

  - by Blanka

  We have a MySQL 5.1.52 Percona Server 11.6 instance that suddenly started logging every single query to the slow query log. The long_query_time configuration is set to 1, yet, suddenly we're seeing every single query (e.g. just saw one that took 0.000563s!). As a result, our log files are growing at an insane pace. We just had to truncate a 180G slow query log file. I tried setting the long_query_time variable to a really large number to see if it stopped altogether (1000000), but same result. show global variables like 'general_log%'; +------------------+--------------------------+ | Variable_name | Value | +------------------+--------------------------+ | general_log | OFF | | general_log_file | /usr2/mysql/data/db4.log | +------------------+--------------------------+ 2 rows in set (0.00 sec) show global variables like 'slow_query_log%'; +---------------------------------------+-------------------------------+ | Variable_name | Value | +---------------------------------------+-------------------------------+ | slow_query_log | ON | | slow_query_log_file | /usr2/mysql/data/db4-slow.log | | slow_query_log_microseconds_timestamp | OFF | +---------------------------------------+-------------------------------+ 3 rows in set (0.00 sec) show global variables like 'long%'; +-----------------+----------+ | Variable_name | Value | +-----------------+----------+ | long_query_time | 1.000000 | +-----------------+----------+ 1 row in set (0.00 sec)

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• SQL SERVER 2008 JOIN hints

  - by Nai

  Hi all, Recently, I was trying to optimise this query UPDATE Analytics SET UserID = x.UserID FROM Analytics z INNER JOIN UserDetail x ON x.UserGUID = z.UserGUID Estimated execution plan show 57% on the Table Update and 40% on a Hash Match (Aggregate). I did some snooping around and came across the topic of JOIN hints. So I added a LOOP hint to my inner join and WA-ZHAM! The new execution plan shows 38% on the Table Update and 58% on an Index Seek. So I was about to start applying LOOP hints to all my queries until prudence got the better of me. After some googling, I realised that JOIN hints are not very well covered in BOL. Therefore... Can someone please tell me why applying LOOP hints to all my queries is a bad idea. I read somewhere that a LOOP JOIN is default JOIN method for query optimiser but couldn't verify the validity of the statement? When are JOIN hints used? When the sh*t hits the fan and ghost busters ain't in town? What's the difference between LOOP, HASH and MERGE hints? BOL states that MERGE seems to be the slowest but what is the application of each hint? Thanks for your time and help people! I'm running SQL Server 2008 BTW. The statistics mentioned above are ESTIMATED execution plans.

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• How can I optimize this subqueried and Joined MySQL Query?

  - by kevzettler

  I'm pretty green on mysql and I need some tips on cleaning up a query. It is used in several variations through out a site. Its got some subquerys derived tables and fun going on. Heres the query: # Query_time: 2 Lock_time: 0 Rows_sent: 0 Rows_examined: 0 SELECT * FROM ( SELECT products . *, categories.category_name AS category, ( SELECT COUNT( * ) FROM distros WHERE distros.product_id = products.product_id) AS distro_count, (SELECT COUNT(*) FROM downloads WHERE downloads.product_id = products.product_id AND WEEK(downloads.date) = WEEK(curdate())) AS true_downloads, (SELECT COUNT(*) FROM views WHERE views.product_id = products.product_id AND WEEK(views.date) = WEEK(curdate())) AS true_views FROM products INNER JOIN categories ON products.category_id = categories.category_id ORDER BY created_date DESC, true_views DESC ) AS count_table WHERE count_table.distro_count > 0 AND count_table.status = 'published' AND count_table.active = 1 LIMIT 0, 8 Heres the explain: +----+--------------------+------------+-------+---------------+-------------+---------+------------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+--------------------+------------+-------+---------------+-------------+---------+------------------------------------+------+----------------------------------------------+ | 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 232 | Using where | | 2 | DERIVED | categories | index | PRIMARY | idx_name | 47 | NULL | 13 | Using index; Using temporary; Using filesort | | 2 | DERIVED | products | ref | category_id | category_id | 4 | digizald_db.categories.category_id | 9 | | | 5 | DEPENDENT SUBQUERY | views | ref | product_id | product_id | 4 | digizald_db.products.product_id | 46 | Using where | | 4 | DEPENDENT SUBQUERY | downloads | ref | product_id | product_id | 4 | digizald_db.products.product_id | 14 | Using where | | 3 | DEPENDENT SUBQUERY | distros | ref | product_id | product_id | 4 | digizald_db.products.product_id | 1 | Using index | +----+--------------------+------------+-------+---------------+-------------+---------+------------------------------------+------+----------------------------------------------+ 6 rows in set (0.04 sec) And the Tables: mysql> describe products; +---------------+--------------------------------------------------+------+-----+-------------------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------------+--------------------------------------------------+------+-----+-------------------+----------------+ | product_id | int(10) unsigned | NO | PRI | NULL | auto_increment | | product_key | char(32) | NO | | NULL | | | title | varchar(150) | NO | | NULL | | | company | varchar(150) | NO | | NULL | | | user_id | int(10) unsigned | NO | MUL | NULL | | | description | text | NO | | NULL | | | video_code | text | NO | | NULL | | | category_id | int(10) unsigned | NO | MUL | NULL | | | price | decimal(10,2) | NO | | NULL | | | quantity | int(10) unsigned | NO | | NULL | | | downloads | int(10) unsigned | NO | | NULL | | | views | int(10) unsigned | NO | | NULL | | | status | enum('pending','published','rejected','removed') | NO | | NULL | | | active | tinyint(1) | NO | | NULL | | | deleted | tinyint(1) | NO | | NULL | | | created_date | datetime | NO | | NULL | | | modified_date | timestamp | NO | | CURRENT_TIMESTAMP | | | scrape_source | varchar(215) | YES | | NULL | | +---------------+--------------------------------------------------+------+-----+-------------------+----------------+ 18 rows in set (0.00 sec) mysql> describe categories -> ; +------------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------------+------------------+------+-----+---------+----------------+ | category_id | int(10) unsigned | NO | PRI | NULL | auto_increment | | category_name | varchar(45) | NO | MUL | NULL | | | parent_id | int(10) unsigned | YES | MUL | NULL | | | category_type_id | int(10) unsigned | NO | | NULL | | +------------------+------------------+------+-----+---------+----------------+ 4 rows in set (0.00 sec) mysql> describe compatibilities -> ; +------------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------------+------------------+------+-----+---------+----------------+ | compatibility_id | int(10) unsigned | NO | PRI | NULL | auto_increment | | name | varchar(45) | NO | | NULL | | | code_name | varchar(45) | NO | | NULL | | | description | varchar(128) | NO | | NULL | | | position | int(10) unsigned | NO | | NULL | | +------------------+------------------+------+-----+---------+----------------+ 5 rows in set (0.01 sec) mysql> describe distros -> ; +------------------+--------------------------------------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------------+--------------------------------------------------+------+-----+---------+----------------+ | id | int(10) unsigned | NO | PRI | NULL | auto_increment | | product_id | int(10) unsigned | NO | MUL | NULL | | | compatibility_id | int(10) unsigned | NO | MUL | NULL | | | user_id | int(10) unsigned | NO | | NULL | | | status | enum('pending','published','rejected','removed') | NO | | NULL | | | distro_type | enum('file','url') | NO | | NULL | | | version | varchar(150) | NO | | NULL | | | filename | varchar(50) | YES | | NULL | | | url | varchar(250) | YES | | NULL | | | virus | enum('READY','PASS','FAIL') | YES | | NULL | | | downloads | int(10) unsigned | NO | | 0 | | +------------------+--------------------------------------------------+------+-----+---------+----------------+ 11 rows in set (0.01 sec) mysql> describe downloads; +------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------+------------------+------+-----+---------+----------------+ | id | int(10) unsigned | NO | PRI | NULL | auto_increment | | product_id | int(10) unsigned | NO | MUL | NULL | | | distro_id | int(10) unsigned | NO | MUL | NULL | | | user_id | int(10) unsigned | NO | MUL | NULL | | | ip_address | varchar(15) | NO | | NULL | | | date | datetime | NO | | NULL | | +------------+------------------+------+-----+---------+----------------+ 6 rows in set (0.01 sec) mysql> describe views -> ; +------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------+------------------+------+-----+---------+----------------+ | id | int(10) unsigned | NO | PRI | NULL | auto_increment | | product_id | int(10) unsigned | NO | MUL | NULL | | | user_id | int(10) unsigned | NO | MUL | NULL | | | ip_address | varchar(15) | NO | | NULL | | | date | datetime | NO | | NULL | | +------------+------------------+------+-----+---------+----------------+ 5 rows in set (0.00 sec)

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• SQL query: Delete a entry which is not present in a join table?

  - by Mestika

  Hi, I’m going to delete all users which has no subscription but I seem to run into problems each time I try to detect the users. My schemas look like this: Users = {userid, name} Subscriptionoffering = {userid, subscriptionname} Now, what I’m going to do is to delete all users in the user table there has a count of zero in the subscriptionoffering table. Or said in other words: All users which userid is not present in the subscriptionoffering table. I’ve tried with different queries but with no result. I’ve tried to say where user.userid <> subscriptionoffering.userid, but that doesn’t seem to work. Do anyone know how to create the correct query? Thanks Mestika

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• Slow MySQL Query not using filesort

  - by Canadaka

  I have a query on my homepage that is getting slower and slower as my database table grows larger. tablename = tweets_cache rows = 572,327 this is the query I'm currently using that is slow, over 5 seconds. SELECT * FROM tweets_cache t WHERE t.province='' AND t.mp='0' ORDER BY t.published DESC LIMIT 50; If I take out either the WHERE or the ORDER BY, then the query is super fast 0.016 seconds. I have the following indexes on the tweets_cache table. PRIMARY published mp category province author So i'm not sure why its not using the indexes since mp, provice and published all have indexes? Doing a profile of the query shows that its not using an index to sort the query and is using filesort which is really slow. possible_keys = mp,province Extra = Using where; Using filesort I tried adding a new multie-colum index with "profiles & mp". The explain shows that this new index listed under "possible_keys" and "key", but the query time is unchanged, still over 5 seconds. Here is a screenshot of the profiler info on the query. http://i355.photobucket.com/albums/r469/canadaka_bucket/slow_query_profile.png Something weird, I made a dump of my database to test on my local desktop so i don't screw up the live site. The same query on my local runs super fast, milliseconds. So I copied all the same mysql startup variables from the server to my local to make sure there wasn't some setting that might be causing this. But even after that the local query runs super fast, but the one on the live server is over 5 seconds. My database server is only using around 800MB of the 4GB it has available. here are the related my.ini settings i'm using default-storage-engine = MYISAM max_connections = 800 skip-locking key_buffer = 512M max_allowed_packet = 1M table_cache = 512 sort_buffer_size = 4M read_buffer_size = 4M read_rnd_buffer_size = 16M myisam_sort_buffer_size = 64M thread_cache_size = 8 query_cache_size = 128M # Try number of CPU's*2 for thread_concurrency thread_concurrency = 8 # Disable Federated by default skip-federated key_buffer = 512M sort_buffer_size = 256M read_buffer = 2M write_buffer = 2M key_buffer = 512M sort_buffer_size = 256M read_buffer = 2M write_buffer = 2M

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• Is there anything else I can do to optimize this MySQL query?

  - by Legend

  I have two tables, Table A with 700,000 entries and Table B with 600,000 entries. The structure is as follows: Table A: +-----------+---------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-----------+---------------------+------+-----+---------+----------------+ | id | bigint(20) unsigned | NO | PRI | NULL | auto_increment | | number | bigint(20) unsigned | YES | | NULL | | +-----------+---------------------+------+-----+---------+----------------+ Table B: +-------------+---------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-------------+---------------------+------+-----+---------+----------------+ | id | bigint(20) unsigned | NO | PRI | NULL | auto_increment | | number_s | bigint(20) unsigned | YES | MUL | NULL | | | number_e | bigint(20) unsigned | YES | MUL | NULL | | | source | varchar(50) | YES | | NULL | | +-------------+---------------------+------+-----+---------+----------------+ I am trying to find if any of the values in Table A are present in Table B using the following code: $sql = "SELECT number from TableA"; $result = mysql_query($sql) or die(mysql_error()); while($row = mysql_fetch_assoc($result)) { $number = $row['number']; $sql = "SELECT source, count(source) FROM TableB WHERE number_s < $number AND number_e > $number GROUP BY source"; $re = mysql_query($sql) or die(mysql_error); while($ro = mysql_fetch_array($re)) { echo $number."\t".$ro[0]."\t".$ro[1]."\n"; } } I was hoping that the query would go fast but then for some reason, it isn't terrible fast. My explain on the select (with a particular value of "number") gives me the following: mysql> explain SELECT source, count(source) FROM TableB WHERE number_s < 1812194440 AND number_e > 1812194440 GROUP BY source; +----+-------------+------------+------+-------------------------+------+---------+------+--------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+------------+------+-------------------------+------+---------+------+--------+----------------------------------------------+ | 1 | SIMPLE | TableB | ALL | number_s,number_e | NULL | NULL | NULL | 696325 | Using where; Using temporary; Using filesort | +----+-------------+------------+------+-------------------------+------+---------+------+--------+----------------------------------------------+ 1 row in set (0.00 sec) Is there any optimization that I can squeeze out of this? I tried writing a stored procedure for the same task but it doesn't even seem to work in the first place... It doesn't give any syntax errors... I tried running it for a day and it was still running which felt odd. CREATE PROCEDURE Filter() Begin DECLARE number BIGINT UNSIGNED; DECLARE x INT; DECLARE done INT DEFAULT 0; DECLARE cur1 CURSOR FOR SELECT number FROM TableA; DECLARE CONTINUE HANDLER FOR NOT FOUND SET done = 1; CREATE TEMPORARY TABLE IF NOT EXISTS Flags(number bigint unsigned, count int(11)); OPEN cur1; hist_loop: LOOP FETCH cur1 INTO number; SELECT count(*) from TableB WHERE number_s < number AND number_e > number INTO x; IF done = 1 THEN LEAVE hist_loop; END IF; IF x IS NOT NULL AND x>0 THEN INSERT INTO Flags(number, count) VALUES(number, x); END IF; END LOOP hist_loop; CLOSE cur1; END

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• Linq-to-sql Compiled Query is returning result from different DataContext

  - by Vladimir Kojic

  Compiled query: public static Func<OperationalDataContext, short, Machine> QueryMachineById = CompiledQuery.Compile((OperationalDataContext db, short machineID) => db.Machines.Where(m => m.MachineID == machineID).SingleOrDefault()); It looks like compiled query is caching Machine object and returning the same object even if query is called from new DataContext (I’m disposing DataContext in the service but I’m getting Machine from previous DataContext). I use POCOs and XML mapping. Revised: It looks like compiled query is returning result from new data context and it is not using the one that I passed in compiled-query. Therefore I can not reuse returned object and link it to another object obtained from datacontext thru non compiled queries. I’m using unit of work pattern : // First Call Using(new DataContext) { Machine from DataContext.Table == machine from cached query } // Do some work // Second Call is failing Using(new DataContext) { Machine from DataContext.Table <> machine from cached query }

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• Light-weight, free, database query tool for Windows?

  - by NoCatharsis

  My question is very similar to the one here except pertaining to a Windows tool. I am also referencing this table and what I found here with a Google search. However, I have no idea which tool would best meet my (very basic) purposes. I am currently using Excel with a basic ODBC connection string to query my database at work. However, Excel is pretty memory-heavy and a basic query tends to throw my computer into a 30 second stall-a-thon. Is there a free tool out there that is light-weight and can serve the same purpose when provided an ODBC connection and a SQL query? Also would prefer that it easily copies over to a spreadsheet as needed.

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• Visual Query Builder

  - by johnnyArt

  If been using "dbForge Query Builder" lately and I'm gotten used to the ease of building and testing a query, specially for those complex ones with inner joins, aliases and multiple conditionals. The expiry date of the trial is about to come, and while wanting to remain on the legal side for this I'd rather not pay the 50USD it costs (although I must say it's pretty cheap for what it does). So my question would be: Are there any free alternatives to replace this visual query builder? I've failed to find any and fear that my only two options are paying for it, or going to the dark side.

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• Query optimization using composite indexes

  - by xmarch

  Many times, during the process of creating a new Coherence application, developers do not pay attention to the way cache queries are constructed; they only check that these queries comply with functional specs. Later, performance testing shows that these perform poorly and it is then when developers start working on improvements until the non-functional performance requirements are met. This post describes the optimization process of a real-life scenario, where using a composite attribute index has brought a radical improvement in query execution times.  The execution times went down from 4 seconds to 2 milliseconds! E-commerce solution based on Oracle ATG – Endeca In the context of a new e-commerce solution based on Oracle ATG – Endeca, Oracle Coherence has been used to calculate and store SKU prices. In this architecture, a Coherence cache stores the final SKU prices used for Endeca baseline indexing. Each SKU price is calculated from a base SKU price and a series of calculations based on information from corporate global discounts. Corporate global discounts information is stored in an auxiliary Coherence cache with over 800.000 entries. In particular, to obtain each price the process needs to execute six queries over the global discount cache. After the implementation was finished, we discovered that the most expensive steps in the price calculation discount process were the global discounts cache query. This query has 10 parameters and is executed 6 times for each SKU price calculation. The steps taken to optimise this query are described below; Starting point Initial query was: String filter = "levelId = :iLevelId AND  salesCompanyId = :iSalesCompanyId AND salesChannelId = :iSalesChannelId "+ "AND departmentId = :iDepartmentId AND familyId = :iFamilyId AND brand = :iBrand AND manufacturer = :iManufacturer "+ "AND areaId = :iAreaId AND endDate >=  :iEndDate AND startDate <= :iStartDate"; Map<String, Object> params = new HashMap<String, Object>(10); // Fill all parameters. params.put("iLevelId", xxxx); // Executing filter. Filter globalDiscountsFilter = QueryHelper.createFilter(filter, params); NamedCache globalDiscountsCache = CacheFactory.getCache(CacheConstants.GLOBAL_DISCOUNTS_CACHE_NAME); Set applicableDiscounts = globalDiscountsCache.entrySet(globalDiscountsFilter); With the small dataset used for development the cache queries performed very well. However, when carrying out performance testing with a real-world sample size of 800,000 entries, each query execution was taking more than 4 seconds. First round of optimizations The first optimisation step was the creation of separate Coherence index for each of the 10 attributes used by the filter. This avoided object deserialization while executing the query. Each index was created as follows: globalDiscountsCache.addIndex(new ReflectionExtractor("getXXX" ) , false, null); After adding these indexes the query execution time was reduced to between 450 ms and 1s. However, these execution times were still not good enough.  Second round of optimizations In this optimisation phase a Coherence query explain plan was used to identify how many entires each index reduced the results set by, along with the cost in ms of executing that part of the query. Though the explain plan showed that all the indexes for the query were being used, it also showed that the ordering of the query parameters was "sub-optimal".  Parameters associated to object attributes with high-cardinality should appear at the beginning of the filter, or more specifically, the attributes that filters out the highest of number records should be placed at the beginning. But examining corporate global discount data we realized that depending on the values of the parameters used in the query the “good” order for the attributes was different. In particular, if the attributes brand and family had specific values it was more optimal to have a different query changing the order of the attributes. Ultimately, we ended up with three different optimal variants of the query that were used in its relevant cases: String filter = "brand = :iBrand AND familyId = :iFamilyId AND departmentId = :iDepartmentId AND levelId = :iLevelId "+ "AND manufacturer = :iManufacturer AND endDate >= :iEndDate AND salesCompanyId = :iSalesCompanyId "+ "AND areaId = :iAreaId AND salesChannelId = :iSalesChannelId AND startDate <= :iStartDate"; String filter = "familyId = :iFamilyId AND departmentId = :iDepartmentId AND levelId = :iLevelId AND brand = :iBrand "+ "AND manufacturer = :iManufacturer AND endDate >=  :iEndDate AND salesCompanyId = :iSalesCompanyId "+ "AND areaId = :iAreaId  AND salesChannelId = :iSalesChannelId AND startDate <= :iStartDate"; String filter = "brand = :iBrand AND departmentId = :iDepartmentId AND familyId = :iFamilyId AND levelId = :iLevelId "+ "AND manufacturer = :iManufacturer AND endDate >= :iEndDate AND salesCompanyId = :iSalesCompanyId "+ "AND areaId = :iAreaId AND salesChannelId = :iSalesChannelId AND startDate <= :iStartDate"; Using the appropriate query depending on the value of brand and family parameters the query execution time dropped to between 100 ms and 150 ms. But these these execution times were still not good enough and the solution was cumbersome. Third and last round of optimizations The third and final optimization was to introduce a composite index. However, this did mean that it was not possible to use the Coherence Query Language (CohQL), as composite indexes are not currently supporte in CohQL. As the original query had 8 parameters using EqualsFilter, 1 using GreaterEqualsFilter and 1 using LessEqualsFilter, the composite index was built for the 8 attributes using EqualsFilter. The final query had an EqualsFilter for the multiple extractor, a GreaterEqualsFilter and a LessEqualsFilter for the 2 remaining attributes.  All individual indexes were dropped except the ones being used for LessEqualsFilter and GreaterEqualsFilter. We were now running in an scenario with an 8-attributes composite filter and 2 single attribute filters. The composite index created was as follows: ValueExtractor[] ve = { new ReflectionExtractor("getSalesChannelId" ), new ReflectionExtractor("getLevelId" ),    new ReflectionExtractor("getAreaId" ), new ReflectionExtractor("getDepartmentId" ),    new ReflectionExtractor("getFamilyId" ), new ReflectionExtractor("getManufacturer" ),    new ReflectionExtractor("getBrand" ), new ReflectionExtractor("getSalesCompanyId" )}; MultiExtractor me = new MultiExtractor(ve); NamedCache globalDiscountsCache = CacheFactory.getCache(CacheConstants.GLOBAL_DISCOUNTS_CACHE_NAME); globalDiscountsCache.addIndex(me, false, null); And the final query was: ValueExtractor[] ve = { new ReflectionExtractor("getSalesChannelId" ), new ReflectionExtractor("getLevelId" ),    new ReflectionExtractor("getAreaId" ), new ReflectionExtractor("getDepartmentId" ),    new ReflectionExtractor("getFamilyId" ), new ReflectionExtractor("getManufacturer" ),    new ReflectionExtractor("getBrand" ), new ReflectionExtractor("getSalesCompanyId" )}; MultiExtractor me = new MultiExtractor(ve); // Fill composite parameters.String SalesCompanyId = xxxx;...AndFilter composite = new AndFilter(new EqualsFilter(me,                   Arrays.asList(iSalesChannelId, iLevelId, iAreaId, iDepartmentId, iFamilyId, iManufacturer, iBrand, SalesCompanyId)),                                     new GreaterEqualsFilter(new ReflectionExtractor("getEndDate" ), iEndDate)); AndFilter finalFilter = new AndFilter(composite, new LessEqualsFilter(new ReflectionExtractor("getStartDate" ), iStartDate)); NamedCache globalDiscountsCache = CacheFactory.getCache(CacheConstants.GLOBAL_DISCOUNTS_CACHE_NAME); Set applicableDiscounts = globalDiscountsCache.entrySet(finalFilter);      Using this composite index the query improved dramatically and the execution time dropped to between 2 ms and  4 ms.  These execution times completely met the non-functional performance requirements . It should be noticed than when using the composite index the order of the attributes inside the ValueExtractor was not relevant.

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• Problem in HQL query

  - by Rupeshit

  I written a query in my sql like this: "select * from table_name order by col_name = 101 desc " Which is working perfectly fine in mysql but when I tried to convert this query into HQl query then it is throwing an exception.So can anyone suggest me that how to write HQL query for the above SQL query.

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• SQLAlchemy custom query column

  - by thrillerator

  I have a declarative table defined like this: class Transaction(Base): __tablename__ = "transactions" id = Column(Integer, primary_key=True) account_id = Column(Integer) transfer_account_id = Column(Integer) amount = Column(Numeric(12, 2)) ... The query should be: SELECT id, (CASE WHEN transfer_account_id=1 THEN -amount ELSE amount) AS amount FROM transactions WHERE account_id = 1 OR transfer_account_id = 1 My code is: query = Transaction.query.filter_by(account_id=1, transfer_account_id=1) query = query.add_column(func.case(...).label("amount") But it doesn't replace the amount column. Been trying to do this with for hours and I don't want to use raw SQL.

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• how to design the query for non-sql database

  - by Benny

  can anyone give some reference for non-sql database query interface design pattern? For sql-based database, the query can be achieved by combining the query token. but for non-sql, how to design the query, given that the query could be very complex.

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• SQL SERVER – Identify Most Resource Intensive Queries – SQL in Sixty Seconds #028 – Video

  - by pinaldave

  During performance tuning conversation the very first question people often ask is what are the queries offending the server or in another word let us identify the queries which are the most resource intensive. The resources are often described as either Memory, CPU or IO. When we talk about the queries the same is applicable for them as well. The query which is doing lots of reads or writes are for sure resource intensive as well query which are taking maximum CPU time. Performance tuning is a very deep subject and we all have our own preference regarding what should be the first step to tuning and what should be looked with the salt of grain. Though there is no denying that a query which uses more resources than what it should be using for sure require tuning. There are many ways to do identify query using intense resources (e.g. Extended events etc) but in this one we will go by simple DMV. There is a small gotcha we all have to remember about usage of DMV is that it only brings back results from existing cache. So if you have a query which is very resource intensive but is not cached or if you have explicitly removed the query from the cache it will be not part of the result returned by this DMV. It is quite possible that a query is aged and removed from the cache if your cache is not huge. If your cache is large you may want to be careful in running this query during business hours as this query itself can be resource intensive. Get Script to identify resource intensive query from Here Related Tips in SQL in Sixty Seconds: SQL SERVER – Find Most Expensive Queries Using DMV Simple Example to Configure Resource Governor – Introduction to Resource Governor SQL SERVER – DMV – sys.dm_exec_query_optimizer_info – Statistics of Optimizer SQL SERVER – Wait Stats – Wait Types – Wait Queues – Day 0 of 28 Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Excel

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• Query Months help

  - by StealthRT

  Hey all i am in need of some helpful tips/advice on how to go about my problem. I have a database that houses a "signup" table. The date for this table is formated as such: 2010-04-03 00:00:00 Now suppose i have 10 records in this database: 2010-04-03 00:00:00 2010-01-01 00:00:00 2010-06-22 00:00:00 2010-02-08 00:00:00 2010-02-05 00:00:00 2010-03-08 00:00:00 2010-09-29 00:00:00 2010-11-16 00:00:00 2010-04-09 00:00:00 2010-05-21 00:00:00 And i wanted to get each months total registers... so following the example above: Jan = 1 Feb = 2 Mar = 1 Apr = 2 May = 1 Jun = 1 Jul = 0 Aug = 0 Sep = 1 Oct = 0 Nov = 1 Dec = 0 Now how can i use a query to do that but not have to use a query like: WHERE left(date, 7) = '2010-01' and keep doing that 12 times? I would like it to be a single query call and just have it place the months visits into a array like so: do until EOF theMonthArray[0] = "total for jan" theMonthArray[1] = "total for feb" theMonthArray[2] = "total for mar" theMonthArray[3] = "total for apr" ...etc loop I just can not think of a way to do that other than the example i posted with the 12 query called-one for each month. This is my query as of right now. Again, this only populates for one month where i am trying to populate all 12 months all at once. SELECT count(idNumber) as numVisits, theAccount, signUpDate, theActive from userinfo WHERE theActive = 'YES' AND idNumber = '0203' AND theAccount = 'SUB' AND left(signUpDate, 7) = '2010-04' GROUP BY idNumber ORDER BY numVisits; The example query above outputs this: numVisits | theAccount | signUpDate | theActive 2 SUB 2010-04-16 00:00:00 YES Which is correct because i have 2 records within the month of April. But again, i am trying to do all 12 months at one time (in a single query) so i do not tax the database server as much when compared to doing 12 different query's... UPDATE I'm looking to do something like along these lines: if NOT rst.EOF if left(rst("signUpDate"), 7) = "2010-01" then theMonthArray[0] = rst("numVisits") end if if left(rst("signUpDate"), 7) = "2010-02" then theMonthArray[1] = rst("numVisits") end if etc etc.... end if Any help would be great! :) David

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• Is there a way to optimize this mysql query...?

  - by SpikETidE

  Hi Everyone... Say, I got these two tables.... Table 1 : Hotels hotel_id hotel_name 1 abc 2 xyz 3 efg Table 2 : Payments payment_id payment_date hotel_id total_amt comission p1 23-03-2010 1 100 10 p2 23-03-2010 2 50 5 p3 23-03-2010 2 200 25 p4 23-03-2010 1 40 2 Now, I need to get the following details from the two tables Given a particular date (say, 23-03-2010), the sum of the total_amt for each of the hotel for which a payment has been made on that particular date. All the rows that has the date 23-03-2010 ordered according to the hotel name A sample output is as follows... +------------+------------+------------+---------------+ | hotel_name | date | total_amt | commission | +------------+------------+------------+---------------+ | * abc | 23-03-2010 | 140 | 12 | +------------+------------+------------+---------------+ |+-----------+------------+------------+--------------+| || paymt_id | date | total_amt | commission || |+-----------+------------+------------+--------------+| || p1 | 23-03-2010 | 100 | 10 || |+-----------+------------+------------+--------------+| || p4 | 23-03-2010 | 40 | 2 || |+-----------+------------+------------+--------------+| +------------+------------+------------+---------------+ | * xyz | 23-03-2010 | 250 | 30 | +------------+------------+------------+---------------+ |+-----------+------------+------------+--------------+| || paymt_id | date | total_amt | commission || |+-----------+------------+------------+--------------+| || p2 | 23-03-2010 | 50 | 5 || |+-----------+------------+------------+--------------+| || p3 | 23-03-2010 | 200 | 25 || |+-----------+------------+------------+--------------+| +------------------------------------------------------+ Above the sample of the table that has to be printed... The idea is first to show the consolidated detail of each hotel, and when the '*' next to the hotel name is clicked the breakdown of the payment details will become visible... But that can be done by some jquery..!!! The table itself can be generated with php... Right now i am using two separate queries : One to get the sum of the amount and commission grouped by the hotel name. The next is to get the individual row for each entry having that date in the table. This is, of course, because grouping the records for calculating sum() returns only one row for each of the hotel with the sum of the amounts... Is there a way to combine these two queries into a single one and do the operation in a more optimized way...?? Hope i am being clear.. Thanks for your time and replies...

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• MS Query returns data inside itself but does not export it to Excel

  - by kappa

  Hi, I'm having a strange problem with Excel and MS Query: I'm using MS Query to run a T-SQL query against a Microsoft SQL Server 2000 and return the results to Excel. To do this, I open Excel, go to Data - Import external data - New database query, select my data source, paste the SQL script in MS Query and click File - Return data to Microsoft Office Excel, leaving all the query options to their defaults. This works fine for many other Excel files, but this time although MS Query shows the correct data when I paste the SQL script, after returning to Excel all I get is the query name in the upper left cell, with no data returned. I fear the cause could be the SQL script, as it contains some advanced functions like union all, UDFs and variables. Here's the script: declare @date smalldatetime set @date = dateadd(day, datediff(day, 0, getdate()), 0) select [date], sum([hours]) as [hours] from ( select [date], [hours] from [server].[dbo].[udf] (84, '2010-01-01', @date) union all select [date], [hours] from [server].[dbo].[udf] (89, '2010-01-01', @date) union all select [date], [hours] from [server].[dbo].[udf] (93, '2010-01-01', @date) ) as [a] group by [date] order by [date] asc I can't get rid of the UDF as inside them are done advanced groupings involving cursors and temporary tables, nor I can remove the variable as the UDF won't accept dateadd(day, datediff(day, 0, getdate()), 0) as parameter. Any ideas? Thanks in advance, Andrea.

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• learning sample of likely() and unlikely() compiler hints

  - by osgx

  Hello How can I demonstrate for students the usability of likely and unlikely compiler hints (__builtin_expect)? Can you write an sample code, which will be several times faster with these hints comparing the code without hints.

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• Is there a word or description for this type of query?

  - by Nick

  We have the requirement to find a result in a collection of records based on a prioritised set of search criteria against a relational db (I'm talking indexed field matching here rather than text search). The way we are thinking about designing the query is to begin with a highly refined and specific set of criteria. If there are no results for this initial query we want to progressively reduce the criteria one by one in order of reducing priority, querying each time such a less specific set of criteria until we find a result we can accept. Alternatively, we have considered starting with a smaller set of criteria and increasing until we have reduced number of results down to the last set. What I would like to know is if an existing term to describe this type of query exists? So that we can look to model our own on existing patterns and use best practice.

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• SQL SERVER – SQL in Sixty Seconds – 5 Videos from Joes 2 Pros Series – SQL Exam Prep Series 70-433

  - by pinaldave

  Joes 2 Pros SQL Server Learning series is indeed fun. Joes 2 Pros series is written for beginners and who wants to build expertise for SQL Server programming and development from fundamental. In the beginning of the series author Rick Morelan is not shy to explain the simplest concept of how to open SQL Server Management Studio. Honestly the book starts with that much basic but as it progresses further Rick discussing about various advanced concepts from query tuning to Core Architecture. This five part series is written with keeping SQL Server Exam 70-433. Instead of just focusing on what will be there in exam, this series is focusing on learning the important concepts thoroughly. This book no way take short cut to explain any concepts and at times, will go beyond the topic at length. The best part is that all the books has many companion videos explaining the concepts and videos. Every Wednesday I like to post a video which explains something in quick few seconds. Today we will go over five videos which I posted in my earlier posts related to Joes 2 Pros series. Introduction to XML Data Type Methods – SQL in Sixty Seconds #015 The XML data type was first introduced with SQL Server 2005. This data type continues with SQL Server 2008 where expanded XML features are available, most notably is the power of the XQuery language to analyze and query the values contained in your XML instance. There are five XML data type methods available in SQL Server 2008: query() – Used to extract XML fragments from an XML data type. value() – Used to extract a single value from an XML document. exist() – Used to determine if a specified node exists. Returns 1 if yes and 0 if no. modify() – Updates XML data in an XML data type. node() – Shreds XML data into multiple rows (not covered in this blog post). [Detailed Blog Post] | [Quiz with Answer] Introduction to SQL Error Actions – SQL in Sixty Seconds #014 Most people believe that when SQL Server encounters an error severity level 11 or higher the remaining SQL statements will not get executed. In addition, people also believe that if any error severity level of 11 or higher is hit inside an explicit transaction, then the whole statement will fail as a unit. While both of these beliefs are true 99% of the time, they are not true in all cases. It is these outlying cases that frequently cause unexpected results in your SQL code. To understand how to achieve consistent results you need to know the four ways SQL Error Actions can react to error severity levels 11-16: Statement Termination – The statement with the procedure fails but the code keeps on running to the next statement. Transactions are not affected. Scope Abortion – The current procedure, function or batch is aborted and the next calling scope keeps running. That is, if Stored Procedure A calls B and C, and B fails, then nothing in B runs but A continues to call C. @@Error is set but the procedure does not have a return value. Batch Termination – The entire client call is terminated. XACT_ABORT – (ON = The entire client call is terminated.) or (OFF = SQL Server will choose how to handle all errors.) [Detailed Blog Post] | [Quiz with Answer] Introduction to Basics of a Query Hint – SQL in Sixty Seconds #013 Query hints specify that the indicated hints should be used throughout the query. Query hints affect all operators in the statement and are implemented using the OPTION clause. Cautionary Note: Because the SQL Server Query Optimizer typically selects the best execution plan for a query, it is highly recommended that hints be used as a last resort for experienced developers and database administrators to achieve the desired results. [Detailed Blog Post] | [Quiz with Answer] Introduction to Hierarchical Query – SQL in Sixty Seconds #012 A CTE can be thought of as a temporary result set and are similar to a derived table in that it is not stored as an object and lasts only for the duration of the query. A CTE is generally considered to be more readable than a derived table and does not require the extra effort of declaring a Temp Table while providing the same benefits to the user. However; a CTE is more powerful than a derived table as it can also be self-referencing, or even referenced multiple times in the same query. A recursive CTE requires four elements in order to work properly: Anchor query (runs once and the results ‘seed’ the Recursive query) Recursive query (runs multiple times and is the criteria for the remaining results) UNION ALL statement to bind the Anchor and Recursive queries together. INNER JOIN statement to bind the Recursive query to the results of the CTE. [Detailed Blog Post] | [Quiz with Answer] Introduction to SQL Server Security – SQL in Sixty Seconds #011 Let’s get some basic definitions down first. Take the workplace example where “Tom” needs “Read” access to the “Financial Folder”. What are the Securable, Principal, and Permissions from that last sentence? A Securable is a resource that someone might want to access (like the Financial Folder). A Principal is anything that might want to gain access to the securable (like Tom). A Permission is the level of access a principal has to a securable (like Read). [Detailed Blog Post] | [Quiz with Answer] Please leave a comment explain which one was your favorite video as that will help me understand what works and what needs improvement. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video

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• Using Query Classes With NHibernate

  - by Liam McLennan

  Even when using an ORM, such as NHibernate, the developer still has to decide how to perform queries. The simplest strategy is to get access to an ISession and directly perform a query whenever you need data. The problem is that doing so spreads query logic throughout the entire application – a clear violation of the Single Responsibility Principle. A more advanced strategy is to use Eric Evan’s Repository pattern, thus isolating all query logic within the repository classes. I prefer to use Query Classes. Every query needed by the application is represented by a query class, aka a specification. To perform a query I: Instantiate a new instance of the required query class, providing any data that it needs Pass the instantiated query class to an extension method on NHibernate’s ISession type. To query my database for all people over the age of sixteen looks like this: [Test] public void QueryBySpecification() { var canDriveSpecification = new PeopleOverAgeSpecification(16); var allPeopleOfDrivingAge = session.QueryBySpecification(canDriveSpecification); } To be able to query for people over a certain age I had to create a suitable query class: public class PeopleOverAgeSpecification : Specification<Person> { private readonly int age; public PeopleOverAgeSpecification(int age) { this.age = age; } public override IQueryable<Person> Reduce(IQueryable<Person> collection) { return collection.Where(person => person.Age > age); } public override IQueryable<Person> Sort(IQueryable<Person> collection) { return collection.OrderBy(person => person.Name); } } Finally, the extension method to add QueryBySpecification to ISession: public static class SessionExtensions { public static IEnumerable<T> QueryBySpecification<T>(this ISession session, Specification<T> specification) { return specification.Fetch( specification.Sort( specification.Reduce(session.Query<T>()) ) ); } } The inspiration for this style of data access came from Ayende’s post Do You Need a Framework?. I am sick of working through multiple layers of abstraction that don’t do anything. Have you ever seen code that required a service layer to call a method on a repository, that delegated to a common repository base class that wrapped and ORMs unit of work? I can achieve the same thing with NHibernate’s ISession and a single extension method. If you’re interested you can get the full Query Classes example source from Github.

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• bind would not work unless allow-query is "any"

  - by adrianTNT

  I have this in /etc/named.conf, I commented the default values and set my own under it. My domain would not load in browser unless I set allow-query to "any", is this OK, what should I edit? If is localhost or 127.0.0.1; 10.0.1.0/24; domain would not load. I tried the 127.. thing because it mentioned it here: http://wiki.mandriva.com/en/Testing:Bind Bind version is 9.7.0-P2-RedHat-9.7.0-5.P2.el6_0.1 OS is CentOS 6.0. options { // listen-on port 53 { 127.0.0.1; }; listen-on port 53 { any; }; //listen-on-v6 port 53 { ::1; }; listen-on-v6 port 53 { any; }; directory "/var/named"; dump-file "/var/named/data/cache_dump.db"; statistics-file "/var/named/data/named_stats.txt"; memstatistics-file "/var/named/data/named_mem_stats.txt"; //allow-query { localhost; }; allow-query { any; }; recursion yes; dnssec-enable yes; dnssec-validation yes; dnssec-lookaside auto; /* Path to ISC DLV key */ bindkeys-file "/etc/named.iscdlv.key"; };

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