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  • Optimize MYSQL Query with Order by

    - by Victor
    Hello, I have seen mysql queries with order by runs slow. Is there any specific way to optimize queries which use order by ? Queries without order by run very fast but with order by its always runs slow. if any one suggest any thing on this as general solutions. Thank You

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  • How to optimize this user ranking query

    - by James Simpson
    I have 2 databases (users, userRankings) for a system that needs to have rankings updated every 10 minutes. I use the following code to update these rankings which works fairly well, but there is still a full table scan involved which slows things down with a few hundred thousand users. mysql_query("TRUNCATE TABLE userRankings"); mysql_query("INSERT INTO userRankings (userid) SELECT id FROM users ORDER BY score DESC"); mysql_query("UPDATE users a, userRankings b SET a.rank = b.rank WHERE a.id = b.userid"); In the userRankings table, rank is the primary key and userid is an index. Both tables are MyISAM (I've wondered if it might be beneficial to make userRankings InnoDB).

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  • SQLAuthority News – BI Quiz Question – How to Optimize Cube? – Hints

    - by pinaldave
    I earlier wrote about SQL BI Quiz over here. The details of the quiz is as following: Working with huge data is very common when it is about Data Warehousing. It is necessary to create Cubes on the data to make it meaningful and consumable. There are cases when retrieving the data from cube takes lots of the time. Let us assume that your cube is returning you data very quickly. Suddenly on one day it is returning the data very slowly. What are the three things will you to diagnose this. After diagnose what you will do to resolve performance issue. Participate in my question over here Here is a couple of hints what I am looking for in answer: How to reach to root of slow performance? Is hardware causing the problem or something else? Is slowness is due to how cube is build and its granularity? Is underlying tables require maintenance? Is there is chance to refractor the process? Are there any tool which can help diagnosis the slowness of the cube? It is not necessary to answer all the question – but something to start with. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Query Tuning Mastery at PASS Summit 2012: The Video

    - by Adam Machanic
    An especially clever community member was kind enough to reverse-engineer the video stream for me, and came up with a direct link to the PASS TV video stream for my Query Tuning Mastery: The Art and Science of Manhandling Parallelism talk, delivered at the PASS Summit last Thursday. I'm not sure how long this link will work , but I'd like to share it for my readers who were unable to see it in person or live on the stream. Start here. Skip past the keynote, to the 149 minute mark. Enjoy!...(read more)

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  • Query Tuning Mastery at PASS Summit 2012: The Video

    - by Adam Machanic
    An especially clever community member was kind enough to reverse-engineer the video stream for me, and came up with a direct link to the PASS TV video stream for my Query Tuning Mastery: The Art and Science of Manhandling Parallelism talk, delivered at the PASS Summit last Thursday. I'm not sure how long this link will work , but I'd like to share it for my readers who were unable to see it in person or live on the stream. Start here. Skip past the keynote, to the 149 minute mark. Enjoy!...(read more)

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  • Query Tuning Mastery at PASS Summit 2012: The Demos

    - by Adam Machanic
    For the second year in a row, I was asked to deliver a 500-level "Query Tuning Mastery" talk in room 6E of the Washington State Convention Center, for the PASS Summit. ( Here's some information about last year's talk, on workspace memory. ) And for the second year in a row, I had to deliver said talk at 10:15 in the morning, in a room used as overflow for the keynote, following a keynote speaker that didn't stop speaking on time. Frustrating! Last Thursday, after very, very quickly setting up and...(read more)

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  • Converting sql query to EF query - nested query in from

    - by vdh_ant
    Hey guys Just wondering how the following sql query would look in linq for Entity Framework... SELECT KPI.* FROM KeyPerformanceIndicator KPI INNER JOIN ( SELECT SPP.SportProgramPlanId FROM SportProgramPlan PSPP INNER JOIN SportProgramPlan ASPP ON (PSPP.SportProgramPlanId = @SportProgramPlanId AND PSPP.StartDate >= ASPP.StartDate AND PSPP.EndDate <= ASPP.EndDate ) AS SPP ON KPI.SportProgramPlanId = SPP.SportProgramPlanId Cheers Anthony

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  • SQL SERVER – Denali Feature – Zoom Query Editor

    - by pinaldave
    SQL Server next version ‘Denali’ is coming up with very neat feature which can be used while presentations, group discussion or for people who prefers large fonts. I have increased the font size to 400 percentage and for the same reason they are very large. You can adjust the font size which is convenient to you. One more reason to go for next version of SQL Server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology

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  • Adding an LOV to a query parameter (executeWithParams)

    - by shay.shmeltzer
    I showed in the past how you can use the executeWithParams operation to build your own query page to filter a view object to show specific rows. I also showed how you can make the parameter fields display as drop down lists of values (selectOneChoice). However this week someone asked me if you can have those parameter fields use the advanced LOV component. Well if you just try and drag the parameter over, you'll see that the LOV option is not there as a drop option. But with a little bit of hacking around you can achieve this. (without actual Java coding). Here is a quick demo:

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  • How can I join this 2 queries?(A select query with join and An unpivot query)

    - by MANG KANOR
    Here are my two queries SELECT EWND.Position, NKey = CASE WHEN ISNULL(Translation.Name, '') = '' THEN EWND.Name ELSE Translation.Name END, Unit = EW_N_DEF.Units FROM EWND INNER JOIN EW_N_DEF ON EW_N_DEF.Nutr_No = EWND.Nutr_No LEFT JOIN Translation ON Translation.CodeMain = EWND.Nutr_no WHERE Translation.CodeTrans = 1 ORDER BY EWND.Position And this is the unpivot one SELECT * FROM (SELECT N1,N2,N3,N4,N5,N6,N7,N8,N9,N10,N11,N12,N13,N14,N15,N16,N17,N18,N19,N20,N21,N22,N23,N24,N25,N26,N27,N28,N29,N30,N31,N32,N33,N34 FROM EWNVal WHERE Code=6035) Test UNPIVOT (Value FOR NUTCODE IN (N1,N2,N3,N4,N5,N6,N7,N8,N9,N10,N11,N12,N13,N14,N15,N16,N17,N18,N19,N20,N21,N22,N23,N24,N25,N26,N27,N28,N29,N30,N31,N32,N33,N34) )AS test Both Queries put out same number of rows but not columns, Is it possible to join this two? I tried the union but it has problems that I cant solve Thanks in advance!

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  • T-SQL Tuesday #13: Clarifying Requirements

    - by Alexander Kuznetsov
    When we transform initial ideas into clear requirements for databases, we typically have to make the following choices: Frequent maintenance vs doing it once. As we are clarifying the requirements, we need to determine whether we want to concinue spending considerable time maintaining the system, or if we want to finish it up and move on to other tasks. Race car maintenance vs installing electric wiring is my favorite analogy for this kind of choice. In some cases we need to sqeeze every last bit...(read more)

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  • Firefox Vimperator - how to offset link hints?

    - by danns87
    I learned how to change the size of hints by modifying fields in the :highlight Hint CSS. I made the hint numbers a big bigger, and as a result they overlap with the hints they're hinting to. (I'd love to post a picture but apparently I'm not entitled to that luxury yet, so I hope I'm clear enough...) How can I introduce an offset or some other sort of buffer between the hints and the links themselves?

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  • what's wrong in File.Exist() method?

    - by Arseny
    Reading some answers with code samples I notice that those where this method mentioned are subjected to criticism. I'm using this method in my code. So I'd like to know if someone give me detailed response whuy this method is not recomemnded and what alternative approaches are?

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  • Function Folding in #PowerQuery

    - by Darren Gosbell
    Originally posted on: http://geekswithblogs.net/darrengosbell/archive/2014/05/16/function-folding-in-powerquery.aspxLooking at a typical Power Query query you will noticed that it's made up of a number of small steps. As an example take a look at the query I did in my previous post about joining a fact table to a slowly changing dimension. It was roughly built up of the following steps: Get all records from the fact table Get all records from the dimension table do an outer join between these two tables on the business key (resulting in an increase in the row count as there are multiple records in the dimension table for each business key) Filter out the excess rows introduced in step 3 remove extra columns that are not required in the final result set. If Power Query was to execute a query like this literally, following the same steps in the same order it would not be overly efficient. Particularly if your two source tables were quite large. However Power Query has a feature called function folding where it can take a number of these small steps and push them down to the data source. The degree of function folding that can be performed depends on the data source, As you might expect, relational data sources like SQL Server, Oracle and Teradata support folding, but so do some of the other sources like OData, Exchange and Active Directory. To explore how this works I took the data from my previous post and loaded it into a SQL database. Then I converted my Power Query expression to source it's data from that database. Below is the resulting Power Query which I edited by hand so that the whole thing can be shown in a single expression: let     SqlSource = Sql.Database("localhost", "PowerQueryTest"),     BU = SqlSource{[Schema="dbo",Item="BU"]}[Data],     Fact = SqlSource{[Schema="dbo",Item="fact"]}[Data],     Source = Table.NestedJoin(Fact,{"BU_Code"},BU,{"BU_Code"},"NewColumn"),     LeftJoin = Table.ExpandTableColumn(Source, "NewColumn"                                   , {"BU_Key", "StartDate", "EndDate"}                                   , {"BU_Key", "StartDate", "EndDate"}),     BetweenFilter = Table.SelectRows(LeftJoin, each (([Date] >= [StartDate]) and ([Date] <= [EndDate])) ),     RemovedColumns = Table.RemoveColumns(BetweenFilter,{"StartDate", "EndDate"}) in     RemovedColumns If the above query was run step by step in a literal fashion you would expect it to run two queries against the SQL database doing "SELECT * …" from both tables. However a profiler trace shows just the following single SQL query: select [_].[BU_Code],     [_].[Date],     [_].[Amount],     [_].[BU_Key] from (     select [$Outer].[BU_Code],         [$Outer].[Date],         [$Outer].[Amount],         [$Inner].[BU_Key],         [$Inner].[StartDate],         [$Inner].[EndDate]     from [dbo].[fact] as [$Outer]     left outer join     (         select [_].[BU_Key] as [BU_Key],             [_].[BU_Code] as [BU_Code2],             [_].[BU_Name] as [BU_Name],             [_].[StartDate] as [StartDate],             [_].[EndDate] as [EndDate]         from [dbo].[BU] as [_]     ) as [$Inner] on ([$Outer].[BU_Code] = [$Inner].[BU_Code2] or [$Outer].[BU_Code] is null and [$Inner].[BU_Code2] is null) ) as [_] where [_].[Date] >= [_].[StartDate] and [_].[Date] <= [_].[EndDate] The resulting query is a little strange, you can probably tell that it was generated programmatically. But if you look closely you'll notice that every single part of the Power Query formula has been pushed down to SQL Server. Power Query itself ends up just constructing the query and passing the results back to Excel, it does not do any of the data transformation steps itself. So now you can feel a bit more comfortable showing Power Query to your less technical Colleagues knowing that the tool will do it's best fold all the  small steps in Power Query down the most efficient query that it can against the source systems.

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  • I have written an SQL query but I want to optimize it [closed]

    - by ankit gupta
    is there any way to do this using minimum no of joins and select? 2 tables are involved in this operation transaction_pci_details and transaction SELECT t6.transaction_pci_details_id, t6.terminal_id, t6.transaction_no, t6.transaction_id, t6.transaction_type, t6.reversal_flag, t6.transmission_date_time, t6.retrivel_ref_no, t6.card_no,t6.card_type, t6.expires_on, t6.transaction_amount, t6.currency_code, t6.response_code, t6.action_code, t6.message_reason_code, t6.merchant_id, t6.auth_code, t6.actual_trans_amnt, t6.bal_card_amnt, t5.sales_person_id FROM TRANSACTION AS t5 INNER JOIN ( SELECT t4.transaction_pci_details_id, t4.terminal_id, t4.transaction_no, t4.transaction_id, t4.transaction_type, t4.reversal_flag, t4.transmission_date_time, t4.retrivel_ref_no, t4.card_no, t4.card_type, t4.expires_on, t4.transaction_amount, t4.currency_code, t4.response_code, t4.action_code, t3.message_reason_code, t4.merchant_id, t4.auth_code, t4.actual_trans_amnt, t4.bal_card_amnt FROM ( SELECT* FROM transaction_pci_details WHERE message_reason_code LIKE '%OUT%'|| message_reason_code LIKE '%FAILED%' /*we can add date here*/ UNION ALL SELECT t2.transaction_pci_details_id, t2.terminal_id, t2.transaction_no, t2.transaction_id, t2.transaction_type, t2.reversal_flag, t2.transmission_date_time, t2.retrivel_ref_no, t2.card_no, t2.card_type, t2.expires_on, t2.transaction_amount, t2.currency_code, t2.response_code, t2.action_code, t2.message_reason_code, t2.merchant_id, t2.auth_code, t2.actual_trans_amnt, t2.bal_card_amnt FROM ( SELECT transaction_id FROM TRANSACTION WHERE transaction_type_id = 8 ) AS t1 INNER JOIN ( SELECT * FROM transaction_pci_details WHERE message_reason_code LIKE '%appro%' /*we can add date here*/ ) AS t2 ON t1.transaction_id = t2.transaction_id ) AS t3 INNER JOIN ( SELECT* FROM transaction_pci_details WHERE action_code LIKE '%REQ%' /*we can add date here*/ ) AS t4 ON t3.transaction_pci_details_id - t4.transaction_pci_details_id = 1 ) AS t6 ON t5.transaction_id = t6.transaction_id

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  • Error 404 after rewrite query strings with htaccess

    - by Cristian
    I'm trying to redirect the URLs of a client's website like this: www.localsite.com/immobile.php?id_immobile=24 In something like this: www.localsite.com/immobile/24.php I'm using this rule in .htaccess but it returns a 404 error page. RewriteEngine On RewriteCond %{QUERY_STRING} ^id_immobile=([0-9]*)$ RewriteRule ^immobile\.php$ http://localsite.com/immobile/%1.php? [L] I have tried many other rules, but none work. What can I do?

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  • Sub query pass through

    - by SQL and the like
    Occasionally in forums and on client sites I see conditional subqueries in statements. This is where the developer has decided that it is only necessary to process some data under a certain condition.  By way of example, something like this : Create Procedure GetOrder @SalesOrderId integer, @CountDetails tinyint as Select SOH.salesorderid , case when @CountDetails = 1 then (Select count(*) from Sales.SalesOrderDetail SOD where SOH.SalesOrderID = SOD.SalesOrderID) end from sales.SalesOrderHeader...(read more)

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  • Does the order of columns in a query matter?

    - by James Simpson
    When selecting columns from a MySQL table, is performance affected by the order that you select the columns as compared to their order in the table (not considering indexes that may cover the columns)? For example, you have a table with rows uid, name, bday, and you have the following query. SELECT uid, name, bday FROM table Does MySQL see the following query any differently and thus cause any sort of performance hit? SELECT uid, bday, name FROM table

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  • Problem with JMX query of Coherence node MBeans visible in JConsole

    - by Quinn Taylor
    I'm using JMX to build a custom tool for monitoring remote Coherence clusters at work. I'm able to connect just fine and query MBeans directly, and I've acquired nearly all the information I need. However, I've run into a snag when trying to query MBeans for specific caches within a cluster, which is where I can find stats about total number of gets/puts, average time for each, etc. The MBeans I'm trying to access programatically are visible when I connect to the remote process using JConsole, and have names like this: Coherence:type=Cache,service=SequenceQueue,name=SEQ%GENERATOR,nodeId=1,tier=back It would make it more flexible if I can dynamically grab all type=Cache MBeans for a particular node ID without specifying all the caches. I'm trying to query them like this: QueryExp specifiedNodeId = Query.eq(Query.attr("nodeId"), Query.value(nodeId)); QueryExp typeIsCache = Query.eq(Query.attr("type"), Query.value("Cache")); QueryExp cacheNodes = Query.and(specifiedNodeId, typeIsCache); ObjectName coherence = new ObjectName("Coherence:*"); Set<ObjectName> cacheMBeans = mBeanServer.queryMBeans(coherence, cacheNodes); However, regardless of whether I use queryMBeans() or queryNames(), the query returns a Set containing... ...0 objects if I pass the arguments shown above ...0 objects if I pass null for the first argument ...all MBeans in the Coherence:* domain (112) if I pass null for the second argument ...every single MBean (128) if I pass null for both arguments The first two results are the unexpected ones, and suggest a problem in the QueryExp I'm passing, but I can't figure out what the problem is. I even tried just passing typeIsCache or specifiedNodeId for the second parameter (with either coherence or null as the first parameter) and I always get 0 results. I'm pretty green with JMX — any insight on what the problem is? (FYI, the monitoring tool will be run on Java 5, so things like JMX 2.0 won't help me at this point.)

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  • Hints to properly design UML class diagram

    - by mic4ael
    Here is the problem. I have just started learning UML and that is why I would like to ask for a few cues from experienced users how I could improve my diagram because I do know it lacks a lot of details, it has mistakes for sure etc. Renovation company hires workers. Each employee has some kind of profession, which is required to work on a particular position. Workers work in groups consisting of at most 15 members - so called production units, which specializes in a specified kind of work. Each production unit is managed by a foreman. Every worker in order to be able to perform job tasks needs proper accessories. There are two kind of tools - light and heavy. To use heavy tools, a worker must have proper privileges. A worker can have at most 3 light tools taken from the warehouse.

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  • MySQL select query result set changes based on column order

    - by user197191
    I have a drupal 7 site using the Views module to back-end site content search results. The same query with the same dataset returns different results from MySQL 5.5.28 to MySQL 5.6.14. The results from 5.5.28 are the correct, expected results. The results from 5.6.14 are not. If, however, I simply move a column in the select statement, the query returns the correct results. Here is the code-generated query in question (modified for readability). I apologize for the length; I couldn't find a way to reproduce it without the whole query: SELECT DISTINCT node_node_revision.nid AS node_node_revision_nid, node_revision.title AS node_revision_title, node_field_revision_field_position_institution_ref.nid AS node_field_revision_field_position_institution_ref_nid, node_revision.vid AS vid, node_revision.nid AS node_revision_nid, node_node_revision.title AS node_node_revision_title, SUM(search_index.score * search_total.count) AS score, 'node' AS field_data_field_system_inst_name_node_entity_type, 'node' AS field_revision_field_position_college_division_node_entity_t, 'node' AS field_revision_field_position_department_node_entity_type, 'node' AS field_revision_field_search_lvl_degree_lvls_node_entity_type, 'node' AS field_revision_field_position_app_deadline_node_entity_type, 'node' AS field_revision_field_position_start_date_node_entity_type, 'node' AS field_revision_body_node_entity_type FROM node_revision node_revision LEFT JOIN node node_node_revision ON node_revision.nid = node_node_revision.nid LEFT JOIN field_revision_field_position_institution_ref field_revision_field_position_institution_ref ON node_revision.vid = field_revision_field_position_institution_ref.revision_id AND (field_revision_field_position_institution_ref.entity_type = 'node' AND field_revision_field_position_institution_ref.deleted = '0') LEFT JOIN node node_field_revision_field_position_institution_ref ON field_revision_field_position_institution_ref.field_position_institution_ref_target_id = node_field_revision_field_position_institution_ref.nid LEFT JOIN field_revision_field_position_cip_code field_revision_field_position_cip_code ON node_revision.vid = field_revision_field_position_cip_code.revision_id AND (field_revision_field_position_cip_code.entity_type = 'node' AND field_revision_field_position_cip_code.deleted = '0') LEFT JOIN node node_field_revision_field_position_cip_code ON field_revision_field_position_cip_code.field_position_cip_code_target_id = node_field_revision_field_position_cip_code.nid LEFT JOIN node node_node_revision_1 ON node_revision.nid = node_node_revision_1.nid LEFT JOIN field_revision_field_position_vacancy_status field_revision_field_position_vacancy_status ON node_revision.vid = field_revision_field_position_vacancy_status.revision_id AND (field_revision_field_position_vacancy_status.entity_type = 'node' AND field_revision_field_position_vacancy_status.deleted = '0') LEFT JOIN search_index search_index ON node_revision.nid = search_index.sid LEFT JOIN search_total search_total ON search_index.word = search_total.word WHERE ( ( (node_node_revision.status = '1') AND (node_node_revision.type IN ('position')) AND (field_revision_field_position_vacancy_status.field_position_vacancy_status_target_id IN ('38')) AND( (search_index.type = 'node') AND( (search_index.word = 'accountant') ) ) AND ( (node_revision.vid=node_node_revision.vid AND node_node_revision.status=1) ) ) ) GROUP BY search_index.sid, vid, score, field_data_field_system_inst_name_node_entity_type, field_revision_field_position_college_division_node_entity_t, field_revision_field_position_department_node_entity_type, field_revision_field_search_lvl_degree_lvls_node_entity_type, field_revision_field_position_app_deadline_node_entity_type, field_revision_field_position_start_date_node_entity_type, field_revision_body_node_entity_type HAVING ( ( (COUNT(*) >= '1') ) ) ORDER BY node_node_revision_title ASC LIMIT 20 OFFSET 0; Again, this query returns different sets of results from MySQL 5.5.28 (correct) to 5.6.14 (incorrect). If I move the column named "score" (the SUM() column) to the end of the column list, the query returns the correct set of results in both versions of MySQL. My question is: Is this expected behavior (and why), or is this a bug? I'm on the verge of reverting my entire environment back to 5.5 because of this.

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  • In MySQL, what is the most effective query design for joining large tables with many to many relatio

    - by lighthouse65
    In our application, we collect data on automotive engine performance -- basically source data on engine performance based on the engine type, the vehicle running it and the engine design. Currently, the basis for new row inserts is an engine on-off period; we monitor performance variables based on a change in engine state from active to inactive and vice versa. The related engineState table looks like this: +---------+-----------+---------------+---------------------+---------------------+-----------------+ | vehicle | engine | engine_state | state_start_time | state_end_time | engine_variable | +---------+-----------+---------------+---------------------+---------------------+-----------------+ | 080025 | E01 | active | 2008-01-24 16:19:15 | 2008-01-24 16:24:45 | 720 | | 080028 | E02 | inactive | 2008-01-24 16:19:25 | 2008-01-24 16:22:17 | 304 | +---------+-----------+---------------+---------------------+---------------------+-----------------+ For a specific analysis, we would like to analyze table content based on a row granularity of minutes, rather than the current basis of active / inactive engine state. For this, we are thinking of creating a simple productionMinute table with a row for each minute in the period we are analyzing and joining the productionMinute and engineEvent tables on the date-time columns in each table. So if our period of analysis is from 2009-12-01 to 2010-02-28, we would create a new table with 129,600 rows, one for each minute of each day for that three-month period. The first few rows of the productionMinute table: +---------------------+ | production_minute | +---------------------+ | 2009-12-01 00:00 | | 2009-12-01 00:01 | | 2009-12-01 00:02 | | 2009-12-01 00:03 | +---------------------+ The join between the tables would be engineState AS es LEFT JOIN productionMinute AS pm ON es.state_start_time <= pm.production_minute AND pm.production_minute <= es.event_end_time. This join, however, brings up multiple environmental issues: The engineState table has 5 million rows and the productionMinute table has 130,000 rows When an engineState row spans more than one minute (i.e. the difference between es.state_start_time and es.state_end_time is greater than one minute), as is the case in the example above, there are multiple productionMinute table rows that join to a single engineState table row When there is more than one engine in operation during any given minute, also as per the example above, multiple engineState table rows join to a single productionMinute row In testing our logic and using only a small table extract (one day rather than 3 months, for the productionMinute table) the query takes over an hour to generate. In researching this item in order to improve performance so that it would be feasible to query three months of data, our thoughts were to create a temporary table from the engineEvent one, eliminating any table data that is not critical for the analysis, and joining the temporary table to the productionMinute table. We are also planning on experimenting with different joins -- specifically an inner join -- to see if that would improve performance. What is the best query design for joining tables with the many:many relationship between the join predicates as outlined above? What is the best join type (left / right, inner)?

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  • SQL SERVER – Signal 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 Signal 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 Signal 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 Signal 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 Signalwait 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 Signal 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 Signal 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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