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  • The 2012 SQLServerCentral/Exceptional DBA Awards Party at the PASS Summit

    The 2012 SQLServerCentral party at the PASS Summit is on and will once again include the awards ceremony for the Exceptional DBA of 2012. Get your tickets now. Keep your database and application development in syncSQL Connect is a Visual Studio add-in that brings your databases into your solution. It then makes it easy to keep your database in sync, and commit to your existing source control system. Find out more.

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  • The PoSh DBA: Grown-Up PowerShell Functions

    Laerte Junior goes step-by-step through the process of tidying up and making more reusable an untidy collection of PowerShell routines, showing how pipelines and advanced functions can make PowerShell more effective in helping to automate many of the working DBA's chores. What are your servers really trying to tell you? Find out with new SQL Monitor 3.0, an easy-to-use tool built for no-nonsense database professionals.For effortless insights into SQL Server, download a free trial today.

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  • The PoSh DBA: Solutions using PowerShell and SQL Server

    PowerShell is worth using when it is the quickest way to providing a solution. For the DBA, it is much more than getting information from SQL Server instances via PowerShell; it can also be run from SQL Server as part of a system that helps with administrative and monitoring tasks. New! SQL Backup Pro 7.2 - easy, automated backup and restoresTry out the latest features and get faster, smaller, verified backups. Download a free trial.

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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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  • What Counts For a DBA: Imagination

    - by drsql
    "Imagination…One little spark, of inspiration… is at the heart, of all creation." – From the song "One Little Spark", by the Sherman Brothers I have a confession to make. Despite my great enthusiasm for databases and programming, it occurs to me that every database system I've ever worked on has been, in terms of its inputs and outputs, downright dull. Most have been glorified e-spreadsheets, many replacing manual systems built on actual spreadsheets. I've created a lot of database-driven software whose main job was to "count stuff"; phone calls, web visitors, payments, donations, pieces of equipment and so on. Sometimes, instead of counting stuff, the database recorded values from other stuff, such as data from sensors or networking devices. Yee hah! So how do we, as DBAs, maintain high standards and high spirits when we realize that so much of our work would fail to raise the pulse of even the most easily excitable soul? The answer lies in our imagination. To understand what I mean by this, consider a role that, in terms of its output, offers an extreme counterpoint to that of the DBA: the Disney Imagineer. Their job is to design Disney's Theme Parks, of which I'm a huge fan. To me this has always seemed like a fascinating and exciting job. What must an Imagineer do, every day, to inspire the feats of creativity that are so clearly evident in those spectacular rides and shows? Here, if ever there was one, is a role where "dull moments" must be rare indeed, surely? I wanted to find out, and so parted with a considerable sum of money for my wife and I to have lunch with one; I reasoned that if I found one small way to apply their secrets to my own career, it would be money well spent. Early in the conversation with our Imagineer (Cindy Cote), the job did indeed sound magical. However, as talk turned to management meetings, budget-wrangling and insane deadlines, I came to the strange realization that, in fact, her job was a lot more like mine than I would ever have guessed. Much like databases, all those spectacular Disney rides bring with them a vast array of complex plumbing, lighting, safety features, and all manner of other "boring bits", kept well out of sight of the end user, but vital for creating the desired experience; and, of course, it is these "boring bits" that take up much of the Imagineer's time. Naturally, there is still a vital part of their job that is spent testing out new ideas, putting themselves in the place of a park visitor, from a 9-year-old boy to a 90-year-old grandmother, and trying to imagine what experiences they'd like to have. It is these small, but vital, sparks of imagination and creativity that have the biggest impact. The real feat of a successful Imagineer is clearly to never to lose sight of this fact, in among all the rote tasks. It is the same for a DBA. Not matter how seemingly dull is the task at hand, try to put yourself in the shoes of the end user, and imagine how your input will affect the experience he or she will have with the database you're building, and how that may affect the world beyond the bits stored in your database. Then, despite the inevitable rush to be "done", find time to go the extra mile and hone the design so that it delivers something as close to that imagined experience as you can get. OK, our output still can't and won't reach the same spectacular heights as the "Journey into The Imagination" ride at EPCOT Theme Park in Orlando, where I first heard "One Little Spark". However, our imaginative sparks and efforts can, and will, make a difference to the user who now feels slightly more at home with a database application, or to the manager holding a report presented with enough clarity to drive an interesting decision or two. They are small victories, but worth having, and appreciated, or at least that's how I imagine it.

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  • What Counts for a DBA: Skill

    - by drsql
    “Practice makes perfect:” right? Well, not exactly. The reality of it all is that this saying is an untrustworthy aphorism. I discovered this in my “younger” days when I was a passionate tennis player, practicing and playing 20+ hours a week. No matter what my passion level was, without some serious coaching (and perhaps a change in dietary habits), my skill level was never going to rise to a level where I could make any money at the sport that involved something other than selling tennis balls at a sporting goods store. My game may have improved with all that practice but I had too many bad practices to overcome. Practice by itself merely reinforces what we know and what we can figure out naturally. The truth is actually closer to the expression used by Vince Lombardi: “Perfect practice makes perfect.” So how do you get to become skilled as a DBA if practice alone isn’t sufficient? Hit the Internet and start searching for SQL training and you can find 100 different sites. There are also hundreds of blogs, magazines, books, conferences both onsite and virtual. But then how do you know who is good? Unfortunately often the worst guide can be to find out the experience level of the writer. Some of the best DBAs are frighteningly young, and some got their start back when databases were stored on stacks of paper with little holes in it. As a programmer, is it really so hard to understand normalization? Set based theory? Query optimization? Indexing and performance tuning? The biggest barrier often is previous knowledge, particularly programming skills cultivated before you get started with SQL. In the world of technology, it is pretty rare that a fresh programmer will gravitate to database programming. Database programming is very unsexy work, because without a UI all you have are a bunch of text strings that you could never impress anyone with. Newbies spend most of their time building UIs or apps with procedural code in C# or VB scoring obvious interesting wins. Making matters worse is that SQL programming requires mastery of a much different toolset than most any mainstream programming skill. Instead of controlling everything yourself, most of the really difficult work is done by the internals of the engine (written by other non-relational programmers…we just can’t get away from them.) So is there a golden road to achieving a high skill level? Sadly, with tennis, I am pretty sure I’ll never discover it. However, with programming it seems to boil down to practice in applying the appropriate techniques for whatever type of programming you are doing. Can a C# programmer build a great database? As long as they don’t treat SQL like C#, absolutely. Same goes for a DBA writing C# code. None of this stuff is rocket science, as long as you learn to understand that different types of programming require different skill sets and you as a programmer must recognize the difference between one of the procedural languages and SQL and treat them differently. Skill comes from practicing doing things the right way and making “right” a habit.

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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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  • Egy DBA napja - Utópia, vagy sem?

    - by lsarecz
    Ma délelott a HOUG BI/DW és DB szakmai napján tartottam egy eloadást arról, hogyan kellene egy DBA-nak dolgoznia manapság. A lényeg az volt, hogy az üzlet legjobb kiszolgálása érdekében célszeru a felhasználók és az alkalmazás oldaláról megközelíteni a kérdést. Azaz monitorozzuk a felhasználók elégedettségét, majd ha valami nem stimmel fúrjunk le alsóbb rétegekbe (MW, DB, OS, HW, Storage, Network), és ott folytassuk a diagnosztikát. Meglepetésemre az eloadást követoen a DB szakosztály vezetoje úgy kommentálta az eloadást, hogy ez még utópisztikus. Ma délután egy a hallgatók között ülo üzemeltetési igazgató e-mail-ben jelezte, hogy ezzel o sem ért egyet, mert ok már most is így üzemeltetnek, még ha nem is minden elemében a Grid Control-t használják. És mi sem bizonyítja jobban, hogy ez az üzemeltetési model nem utópia, mint hogy az Oracle Enterprise Manager 11g tökéletes támogatást ad minderre. Akit ezek után érdekel az eloadásom, az innen letöltheti: 1. fele, 2. fele.

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  • DBA Best Practices: A Blog Series

    - by Argenis
      Introduction After the success of the “Demystifying DBA Best Practices” Pre-Conference that my good friend Robert Davis, a.k.a. SQLSoldier [Blog|Twitter] and I delivered at multiple events, including the PASS Summit 2012, I have decided to blog about some of the topics discussed at the Pre-Con. My thanks go to Robert for agreeing to share this content with the larger SQL Server community. This will be a rather lengthy blog series - and as in the Pre-Con, I expect a lot of interaction and feedback. Make sure you throw in your two cents in the comments section of every blog post. First topic that I’ll be discussing in this blog series: The thing of utmost importance for any Database Administrator: the data. Let’s discuss the importance of backups and a solid restore strategy. Care to share your thoughts on this subject in the comments section below?

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  • DBA Best Practices: A Blog Series

    - by Argenis
      Introduction After the success of the “Demystifying DBA Best Practices” Pre-Conference that my good friend Robert Davis, a.k.a. SQLSoldier [Blog|Twitter] and I delivered at multiple events, including the PASS Summit 2012, I have decided to blog about some of the topics discussed at the Pre-Con. My thanks go to Robert for agreeing to share this content with the larger SQL Server community. This will be a rather lengthy blog series - and as in the Pre-Con, I expect a lot of interaction and feedback. Make sure you throw in your two cents in the comments section of every blog post. First topic that I’ll be discussing in this blog series: The thing of utmost importance for any Database Administrator: the data. Let’s discuss the importance of backups and a solid restore strategy. Care to share your thoughts on this subject in the comments section below?

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  • Free ebook: Troubleshooting SQL Server: A Guide for the Accidental DBA

    We spend much of our working life helping solve SQL Server-related performance problems, hands-on, during consulting, or on online forums. We've seen a few weird-and-wonderful issues but, mainly, it’s the same problems and misconceptions time-and-again. This is our attempt to describe, diagnose, and solve the most common problems with SQL Server 2005, 2008, and 2008 R2. And it's free. "It really helped us isolate where we were experiencing a bottleneck"- John Q Martin, SQL Server DBA. Get started with SQL Monitor today to solve tricky performance problems - download a free trial

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  • SQL?????!????????????????? ~ DBA????APEX

    - by Yuichi.Hayashi
    Oracle Application Express(Oracle APEX)????????????Web????????????????DBA??????·???????????????? SQL?????!????·????????????????????? SQL????????????SQL??????????????????????? Oracle Apex???????????????????????????????SQL??????????????????????????????????? Oracle DB10g????????????iSQLPLUS????????????????????????????????????? SQL?????????CSV???????????? ??·?????????????????????? ????: SQL??????????? ??????: SQL??????????? ?DESCRIBE?: ??????SQL?: SQL?????????????????????????????? ????: ?????SQL???????????? APEX?????????????????????????????????? APEX(Oracle Application Express)????~??????????????????????

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  • ????:???????DBA??Linux,IFRS,??????

    - by atsuko.nishihata
    ?????????????????????????!! 2010?5?25?(?)?????????????????????????????????????IT?????????????????????????? Day?4???????????????????????10???????????????????????????????????????????!! 9:30-10:30 (9:15-????) ???????????? -??????????????? EPM?BI???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? 11:00-12:00 (10:45-????) ????????????? ??????Oracle?????????Linux?? ???Oracle??Linux??????????????????????Linux·???????????IT???????????????????????????DBA????Linux????????????????????????????????????????????????????????????Linux????????????10???????????????????????????? 13:30-14:30 (13:15-????) ??????IFRS?????????????? ??????????????????????????????????????????????????IFRS??????????????????????????????????????????????????????????????????????????? 15:00-16:00 (14:45-????) ??????????????!???·?????????? ?????????????????????????????????Oracle??????????????????????????????????????????????????????Oracle??????????????????????????????????????????????????????????? ????????????????!! ·Oracle Direct Seminar????? ·?????????:?????? ·???????????FAQ

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  • ????!DBA & Developer Day ??????????????????????????????!

    - by OTN-J Master
    ???(11?20?)??????????????????????????????Oracle DBA & Developer Day????????????????????????????????????????????????? ???????????????????????????????????·?????????????????????????????????????????????????????????????????? ???????????????”?”????????????????????????????????????????????????????????????????????????? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?????????????????????????????????????????!! OTN???????????????24?????????????????????????????????????????????·?????????????????????????????????????????12???????????????????OTN???????????????????????????? ???????·?????(MyProfile??)??????????????????????OTN???????????????????????·????????????????????????????????????·????????????????????????????? (?????????) >> OTN????????????????????

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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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  • 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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  • I'm blogging again, and about time too

    - by fatherjack
    No, seriously, this one is about time. I recently had an issue in a work database where a query was giving random results, sometimes the query would return a row and other times it wouldn't. There was quite a bit of work distilling the query down to find the reason for this and I'll try to explain by demonstrating what was happening by using some sample data in a table with rather a contrived use case. Let's assume we have a table that is designed to have a start and end date for something, maybe...(read more)

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