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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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  • 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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  • 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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  • WAN Optimization for Small Office/Home Office

    - by TiernanO
    I have been reading up on WAN optimization for the last while, mostly out of interest of speeding up my own internet connections, but also to speed up the office internet connection. At home, I have 2 cable modems plugged into a RouterBoard RB750, which load balances the connections. In the office, we have a single connection into a NetGear router. Most of the WAN Optimization products I have seen, seem to be prohibitively expensive, but also seem to be based on the idea of having multiple branches around the world. What I am looking for, ideally, is as follows: software install: I am "guessing" I need to install it in 2 places: one in the office or house, and one in "the cloud". any connections going to, say, The US (we are in Europe, but our backup's live in the US currently, which would be something important to speed up) would be "tunnelled" though the Optimizer. If downloading or uploading large files, open multiple connections between both "the cloud" and the optimizer... This is where a lot of speed could be gained. finally, for items not compressed, they would be compressed on the cloud side of things, also items that are already on the optimizer could be not sent again. kind of like RSync or Proxy servers... So, is there something that can be done? Is it available using off the shelf components (some magic script with SSH, Squid, Linux and duct tape) or is it something that needs to be purchased? or even an Open Source Project that does 90% of what i am asking?

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  • Why would using a Temp table be faster than a nested query?

    - by Mongus Pong
    We are trying to optimise some of our queries. One query is doing the following: SELECT t.TaskID, t.Name as Task, '' as Tracker, t.ClientID, (<complex subquery>) Date, INTO [#Gadget] FROM task t SELECT TOP 500 TaskID, Task, Tracker, ClientID, dbo.GetClientDisplayName(ClientID) as Client FROM [#Gadget] order by CASE WHEN Date IS NULL THEN 1 ELSE 0 END , Date ASC DROP TABLE [#Gadget] (I have removed the complex subquery, cos I dont think its relevant other than to explain why this query has been done as a two stage process.) Now I would have thought it would be far more efficient to merge this down into a single query using subqueries as : SELECT TOP 500 TaskID, Task, Tracker, ClientID, dbo.GetClientDisplayName(ClientID) FROM ( SELECT t.TaskID, t.Name as Task, '' as Tracker, t.ClientID, (<complex subquery>) Date, FROM task t ) as sub order by CASE WHEN Date IS NULL THEN 1 ELSE 0 END , Date ASC This would give the optimiser better information to work out what was going on and avoid any temporary tables. It should be faster. But it turns out it is a lot slower. 8 seconds vs under 5 seconds. I cant work out why this would be the case as all my knowledge of databases imply that subqueries would always be faster than using temporary tables. Can anyone explain what could be going on!?!?

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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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  • SQL Server 2008 Optimization

    - by hgulyan
    I've learned today, if you append to your query OPTION (MAXDOP 0) your query will run on multiple processors and if it's huge query, query will perform faster. I know general guidelines on query optimizations (using indexes, selecting only needed fields etc.), my question is about SQL Server optimization. Maybe changing some options in configurations or anything else. What guidelines are there for SQL Server Optimization? Thank you.

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  • Offline web font optimization tool

    - by avok00
    I have a few web fonts on my web site that I want to reduce in size. I tried http://www.fontsquirrel.com/fontface/generator with very good results, but I need an offline professional tool to rely on. Can somebody recommend such a tool? I am not a specialist font creator, so I need something like a wizard that can guide me through font optimization. Any suggestion is much appretiated! EDIT: To make myself more clear, I need a font subsetting tool

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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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  • The explain tells that the query is awful (it doesn't use a single key) but I'm using LIMIT 1. Is th

    - by Ricardo
    The explain command with the query: explain SELECT * FROM leituras WHERE categorias_id=75 AND textos_id=190304 AND cookie='3f203349ce5ad3c67770ebc882927646' AND endereco_ip='127.0.0.1' LIMIT 1 The result: id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE leituras ALL (null) (null) (null) (null) 1022597 Using where Will it make any difference adding some keys on the table? Even that the query will always return only one row.

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  • Skype Optimization - Port Forwarding on a Router

    - by user19185
    I was watching this Video which talked about using port-forwarding to optimize your LAN for skype calls. According to the video, as explained in the first couple of minutes in the video, the reason you would need optimization is because if the person your call has a firewall setup, your connection has to go-through a third-party computer to connect to them. I believe I stated this correct (maybe not). None the less, my question is this: do both parties on the call need to enable port forwarding to optimize skype, or just one party (person)?

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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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  • Why is Postgres doing a Hash in this query?

    - by Claudiu
    I have two tables: A and P. I want to get information out of all rows in A whose id is in a temporary table I created, tmp_ids. However, there is additional information about A in the P table, foo, and I want to get this info as well. I have the following query: SELECT A.H_id AS hid, A.id AS aid, P.foo, A.pos, A.size FROM tmp_ids, P, A WHERE tmp_ids.id = A.H_id AND P.id = A.P_id I noticed it going slowly, and when I asked Postgres to explain, I noticed that it combines tmp_ids with an index on A I created for H_id with a nested loop. However, it hashes all of P before doing a Hash join with the result of the first merge. P is quite large and I think this is what's taking all the time. Why would it create a hash there? P.id is P's primary key, and A.P_id has an index of its own.

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  • Nginx and 1000 WordPress Installs - Optimization

    - by GTE
    Hey, I'm trying to create a rather unusual (imo) configuration where I have: nginx php-fastcgi mysql 1000 seperate WordPress installs (with WP Super Cache). Each WP install corresponds to a seperate subdomain. Furthermore, I have 1000 cron jobs being called every hour that in turn call a WP plugin (using wget) which retrieves data from an API and posts it to the respective blog. This is all being run on a virtual server with 1024MB of RAM, 4 shared processors, etc. The server is not doing well, especially during the times that the cron jobs are being executed. Nginx constantly throws 504 errors and the site has a significant lag. 1) Am I crazy for having 1000 individual WP installs? Should I be using WP-MU and will this help significantly? (I have certain plugin restrictions that I prefer having seperate installs but could switch if need be.) 2) Instead of having 1000 unique cron jobs - should be calling say a bash script that will then process the 1000 HTTP requests I need? Could this be done in a succesive order instead of a sequential one? 3) Any other kind of suggestion you may have for optimization? Should I be proxying to Apache instead of just using nginx, etc. Any kind of advice would be appreciated. Thanks in advance

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  • Local Search Engine Optimization - Why Use Local SEO?

    Local search engine optimization is the new optimization technique to help improve ones local efforts in your hometown or local areas a business does business. Local SEO is more useful for companies trying to gain new business within a smaller target range of 5-15 miles sometimes less sometimes more depending on the products or services one might provide to consumers. Local Search Engine Optimization and Normal Search Engine Optimization differs so hiring someone who specializes in local SEO is very important.

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  • Search Engine Optimization And Other Web Services

    The SEO (Search Engine Optimization) involves an On-Page Optimization through which the different actions being done on the site so as to make the data and content presentable and relevant with a tidy and appealing display for the readers who frequently visit it to gain info on their part of interest and also for the Search Engines wanderers who want to register them. The search engine marketing Company, SEO Services renders a good quality Search Engine Optimization, also Social media optimization and many different types of marketing Solutions for the web business.

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