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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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  • 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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  • Display root node of Hierarchical Tree using ADF - EJB DC

    - by arul.wilson(at)oracle.com
    Displaying Employee (HR schema) records in Hierarchical Tree can be achieved in ADF-BC by creating custom VO and a Viewlink for displaying root node. This can be more easily done using  EJB-DC by just introducing a NamedQuery to get the root node.Here you go to get this scenario working.Create DB connection based on HR schema.Create Entity Bean from Employees Table.Add custom NamedQuery to Employees.java bean, this named query is responsible for fetching the root node (King in this example). @NamedQueries({  @NamedQuery(name = "Employees.findAll", query = "select o from Employees o"),  @NamedQuery(name = "Employees.findRootEmp", query = "select p from Employees p where p.employees is null")}) Create Stateless Session Bean and expose the Named Queries through the Session Facade.Create Datacontrol from SessionBean local interface.Create jspx page in ViewController project.Drop employeesFindRootEmp from Data Controls Palette as ADF Tree.Add employeesList as Tree level rule.Run page to see the hierarchical tree with root node as 'King'

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  • Optimizing hierarchical transform

    - by Geotarget
    I'm transforming objects in 3D space by transforming each vector with the object's 4x4 transform matrix. In order to achieve hierarchical transform, I transform the child by its own matrix, and then the child by the parent matrix. This becomes costly because objects deeper in the display tree have to be transformed by all the parent objects. This is what's happening, in summary: Root -- transform its verts by Root matrix Parent -- transform its verts by Parent, Root matrix Child -- transform its verts by Child, Parent, Root matrix Is there a faster way to transform vertices to achieve hierarchical transform? What If I first concatenated each transform matrix with the parent matrices, and then transform verts by that final resulting matrix, would that work and wouldn't that be faster? Root -- transform its verts by Root matrix Parent -- concat Parent, Root matrices, transform its verts by Concated matrix Child -- concat Child, Parent, Root matrices, transform its verts by Concated matrix

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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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  • Best method to search hierarchical data

    - by WDuffy
    I'm looking at building a facility which allows querying for data with hierarchical filtering. I have a few ideas how I'm going to go about it but was wondering if there are any recommendations or suggestions that might be more efficient. As an example imagine that a user is searching for a job. The job areas would be as follows. 1: Scotland 2: --- West Central 3: ------ Glasgow 4: ------ Etc 5: --- North East 6: ------ Ayrshire 7: ------ Etc A user can search specific (i.e. Glasgow) or in a larger area (i.e. Scotland). The two approaches I am considering are: keep a note of children in the database for each record (i.e. cat 1 would have 2, 3, 4 in its children field) and query against that record with a SELECT * FROM Jobs WHERE Category IN Areas.childrenField. Use a recursive function to find all results who have a relation to the selected area. The problems I see from both are: Holding this data in the db will mean having to keep track of all changes to structure. Recursion is slow and inefficent. Any ideas, suggestion or recommendations on the best approach? I'm using C# ASP.NET with MSSQL 2005 DB.

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  • Advantages of relational databases over VSAM, ISAM and hierarchical data stores

    - by llaszews
    When migrating companies from legacy environments to the cloud, invariably you run into older hierarchical, flat file, VSAM, ISAM and other legacy data stores. There are many advantages to moving these databases into a relational database structure. The most important which is that most cloud providers run on relational database models. AWS, for example, supports Oracle, SQL Server, and MySQL. The top three 'other reasons' for moving to a relational database are: 1. Data Access – Thousands of database access tools from query creation to business intelligence. 2. Management and monitoring – Hundreds of tools for management and monitoring of the database. 3. Leverage all the free tools from relational database vendors. Free Oracle database tools include: -Application Express – WYSIWIG browse based application development and deployment. -SQL Developer – SQL and PL/SQL development. Database object maintenance. What is interesting is that Big Data NoSQL databases and XML databases are taking us back to the days of VSAM (key value databases) with NoSQL and IMS (hierarchical) with XML databases?

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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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  • 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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  • 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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  • Do you play Sudoku ?

    - by Gilles Haro
    Did you know that 11gR2 database could solve a Sudoku puzzle with a single query and, most of the time, and this in less than a second ? The following query shows you how ! Simply pass a flattened Sudoku grid to it a get the result instantaneously ! col "Solution" format a9 col "Problem" format a9 with Iteration( initialSudoku, Step, EmptyPosition ) as ( select initialSudoku, InitialSudoku, instr( InitialSudoku, '-' )        from ( select '--64----2--7-35--1--58-----27---3--4---------4--2---96-----27--7--58-6--3----18--' InitialSudoku from dual )    union all    select initialSudoku        , substr( Step, 1, EmptyPosition - 1 ) || OneDigit || substr( Step, EmptyPosition + 1 )         , instr( Step, '-', EmptyPosition + 1 )      from Iteration         , ( select to_char( rownum ) OneDigit from dual connect by rownum <= 9 ) OneDigit     where EmptyPosition > 0       and not exists          ( select null              from ( select rownum IsPossible from dual connect by rownum <= 9 )             where OneDigit = substr( Step, trunc( ( EmptyPosition - 1 ) / 9 ) * 9 + IsPossible, 1 )   -- One line must contain the 1-9 digits                or OneDigit = substr( Step, mod( EmptyPosition - 1, 9 ) - 8 + IsPossible * 9, 1 )      -- One row must contain the 1-9 digits                or OneDigit = substr( Step, mod( trunc( ( EmptyPosition - 1 ) / 3 ), 3 ) * 3           -- One square must contain the 1-9 digits                            + trunc( ( EmptyPosition - 1 ) / 27 ) * 27 + IsPossible                            + trunc( ( IsPossible - 1 ) / 3 ) * 6 , 1 )          ) ) select initialSudoku "Problem", Step "Solution"    from Iteration  where EmptyPosition = 0 ;   The Magic thing behind this is called Recursive Subquery Factoring. The Oracle documentation gives the following definition: If a subquery_factoring_clause refers to its own query_name in the subquery that defines it, then the subquery_factoring_clause is said to be recursive. A recursive subquery_factoring_clause must contain two query blocks: the first is the anchor member and the second is the recursive member. The anchor member must appear before the recursive member, and it cannot reference query_name. The anchor member can be composed of one or more query blocks combined by the set operators: UNION ALL, UNION, INTERSECT or MINUS. The recursive member must follow the anchor member and must reference query_name exactly once. You must combine the recursive member with the anchor member using the UNION ALL set operator. This new feature is a replacement of this old Hierarchical Query feature that exists in Oracle since the days of Aladdin (well, at least, release 2 of the database in 1977). Everyone remembers the old syntax : select empno, ename, job, mgr, level      from   emp      start with mgr is null      connect by prior empno = mgr; that could/should be rewritten (but not as often as it should) as withT_Emp (empno, name, level) as        ( select empno, ename, job, mgr, level             from   emp             start with mgr is null             connect by prior empno = mgr        ) select * from   T_Emp; which uses the "with" syntax, whose main advantage is to clarify the readability of the query. Although very efficient, this syntax had the disadvantage of being a Non-Ansi Sql Syntax. Ansi-Sql version of Hierarchical Query is called Recursive Subquery Factoring. As of 11gR2, Oracle got compliant with Ansi Sql and introduced Recursive Subquery Factoring. It is basically an extension of the "With" clause that enables recursion. Now, the new syntax for the query would be with T_Emp (empno, name, job, mgr, hierlevel) as       ( select E.empno, E.ename, E.job, E.mgr, 1 from emp E where E.mgr is null         union all         select E.empno, E.ename, E.job, E.mgr, T.hierlevel + 1from emp E                                                                                                            join T_Emp T on ( E.mgr = T.empno ) ) select * from   T_Emp; The anchor member is a replacement for the "start with" The recursive member is processed through iterations. It joins the Source table (EMP) with the result from the Recursive Query itself (T_Emp) Each iteration works with the results of all its preceding iterations.     Iteration 1 works on the results of the first query     Iteration 2 works on the results of Iteration 1 and first query     Iteration 3 works on the results of Iteration 1, Iteration 2 and first query. So, knowing that, the Sudoku query it self-explaining; The anchor member contains the "Problem" : The Initial Sudoku and the Position of the first "hole" in the grid. The recursive member tries to replace the considered hole with any of the 9 digit that would satisfy the 3 rules of sudoku Recursion progress through the grid until it is complete.   Another example :  Fibonaccy Numbers :  un = (un-1) + (un-2) with Fib (u1, u2, depth) as   (select 1, 1, 1 from dual    union all    select u1+u2, u1, depth+1 from Fib where depth<10) select u1 from Fib; Conclusion Oracle brings here a new feature (which, to be honest, already existed on other concurrent systems) and extends the power of the database to new boundaries. It’s now up to developers to try and test it and find more useful application than solving puzzles… But still, solving a Sudoku in less time it takes to say it remains impressive… Interesting links: You might be interested by the following links which cover different aspects of this feature Oracle Documentation Lucas Jellema 's Blog Fibonaci Numbers

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