Search Results

Search found 28685 results on 1148 pages for 'query performance'.

Page 45/1148 | < Previous Page | 41 42 43 44 45 46 47 48 49 50 51 52  | Next Page >

  • Oracle: Difference in execution plans between databases

    - by Will
    Hello, I am comparing queries my development and production database. They are both Oracle 9i, but almost every single query has a completely different execution plan depending on the database. All tables/indexes are the same, but the dev database has about 1/10th the rows for each table. On production, the query execution plan it picks for most queries is different from development, and the cost is somtimes 1000x higher. Queries on production also seem to be not using the correct indexes for queries in some cases (full table access). I have ran dbms_utility.analyze schema on both databases recently as well in the hopes the CBO would figure something out. Is there some other underlying oracle configuration that could be causing this? I am a developer mostly so this kind of DBA analysis is fairly confusing at first..

    Read the article

  • Columnstore Case Study #1: MSIT SONAR Aggregations

    - by aspiringgeek
    Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

    Read the article

  • Columnstore Case Study #1: MSIT SONAR Aggregations

    - by aspiringgeek
    Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

    Read the article

  • Using Oracle hint "FIRST_ROWS" to improve Oracle database performances

    - by bobetko
    I have a statement that runs on Oracle database server. The statement has about 5 joins and there is nothing unusual there. It looks pretty much like below: SELECT field1, field2, field3, ... FROM table1, table2, table3, table4, table5 WHERE table1.id = table2.id AND table2.id = table3.id AND ... table5.userid = 1 The problem (and what is interesting) is that statement for userid = 1 takes 1 second to return 590 records. Statement for userid = 2 takes around 30 seconds to return 70 records. I don't understand why is difference so big. It seems that different execution plan is chosen for statement with userid = 1 and different for userid = 2. After I implemented Oracle Hint FIRST_ROW, performance become significantly better. Both statements (for both ids 1 and 2) produce return in under 1 second. SELECT /*+ FIRST_ROWS */ field1, field2, field3, ... FROM table1, table2, table3, table4, table5 WHERE table1.id = table2.id AND table2.id = table3.id AND ... table5.userid = 1 Questions: 1) What are possible reasons for bad performance when userid = 2 (when hint is not used)? 2) Why would execution plan be different for one vs another statement (when hint is not used)? 3) Is there anything that I should be careful about when deciding to add this hint to my queries? Thanks

    Read the article

  • MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1

    - by Mat Keep
    0 0 1 893 5092 Homework 42 11 5974 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 to deliver over 8x higher performance than the previous MySQL Cluster 7.1 release on a recent benchmark What’s New in MySQL Cluster 7.2 MySQL Cluster 7.2 was released as GA (Generally Available) in February 2012, delivering many enhancements to performance on complex queries, new NoSQL Key / Value API, cross-data center replication and ease-of-use. These enhancements are summarized in the Figure below, and detailed in the MySQL Cluster New Features whitepaper Figure 1: Next Generation Web Services, Cross Data Center Replication and Ease-of-Use Once of the key enhancements delivered in MySQL Cluster 7.2 is extensions made to the multi-threading processes of the data nodes. Multi-Threaded Data Node Extensions The MySQL Cluster 7.2 data node is now functionally divided into seven thread types: 1) Local Data Manager threads (ldm). Note – these are sometimes also called LQH threads. 2) Transaction Coordinator threads (tc) 3) Asynchronous Replication threads (rep) 4) Schema Management threads (main) 5) Network receiver threads (recv) 6) Network send threads (send) 7) IO threads Each of these thread types are discussed in more detail below. MySQL Cluster 7.2 increases the maximum number of LDM threads from 4 to 16. The LDM contains the actual data, which means that when using 16 threads the data is more heavily partitioned (this is automatic in MySQL Cluster). Each LDM thread maintains its own set of data partitions, index partitions and REDO log. The number of LDM partitions per data node is not dynamically configurable, but it is possible, however, to map more than one partition onto each LDM thread, providing flexibility in modifying the number of LDM threads. The TC domain stores the state of in-flight transactions. This means that every new transaction can easily be assigned to a new TC thread. Testing has shown that in most cases 1 TC thread per 2 LDM threads is sufficient, and in many cases even 1 TC thread per 4 LDM threads is also acceptable. Testing also demonstrated that in some instances where the workload needed to sustain very high update loads it is necessary to configure 3 to 4 TC threads per 4 LDM threads. In the previous MySQL Cluster 7.1 release, only one TC thread was available. This limit has been increased to 16 TC threads in MySQL Cluster 7.2. The TC domain also manages the Adaptive Query Localization functionality introduced in MySQL Cluster 7.2 that significantly enhanced complex query performance by pushing JOIN operations down to the data nodes. Asynchronous Replication was separated into its own thread with the release of MySQL Cluster 7.1, and has not been modified in the latest 7.2 release. To scale the number of TC threads, it was necessary to separate the Schema Management domain from the TC domain. The schema management thread has little load, so is implemented with a single thread. The Network receiver domain was bound to 1 thread in MySQL Cluster 7.1. With the increase of threads in MySQL Cluster 7.2 it is also necessary to increase the number of recv threads to 8. This enables each receive thread to service one or more sockets used to communicate with other nodes the Cluster. The Network send thread is a new thread type introduced in MySQL Cluster 7.2. Previously other threads handled the sending operations themselves, which can provide for lower latency. To achieve highest throughput however, it has been necessary to create dedicated send threads, of which 8 can be configured. It is still possible to configure MySQL Cluster 7.2 to a legacy mode that does not use any of the send threads – useful for those workloads that are most sensitive to latency. The IO Thread is the final thread type and there have been no changes to this domain in MySQL Cluster 7.2. Multiple IO threads were already available, which could be configured to either one thread per open file, or to a fixed number of IO threads that handle the IO traffic. Except when using compression on disk, the IO threads typically have a very light load. Benchmarking the Scalability Enhancements The scalability enhancements discussed above have made it possible to scale CPU usage of each data node to more than 5x of that possible in MySQL Cluster 7.1. In addition, a number of bottlenecks have been removed, making it possible to scale data node performance by even more than 5x. Figure 2: MySQL Cluster 7.2 Delivers 8.4x Higher Performance than 7.1 The flexAsynch benchmark was used to compare MySQL Cluster 7.2 performance to 7.1 across an 8-node Intel Xeon x5670-based cluster of dual socket commodity servers (6 cores each). As the results demonstrate, MySQL Cluster 7.2 delivers over 8x higher performance per data nodes than MySQL Cluster 7.1. More details of this and other benchmarks will be published in a new whitepaper – coming soon, so stay tuned! In a following blog post, I’ll provide recommendations on optimum thread configurations for different types of server processor. You can also learn more from the Best Practices Guide to Optimizing Performance of MySQL Cluster Conclusion MySQL Cluster has achieved a range of impressive benchmark results, and set in context with the previous 7.1 release, is able to deliver over 8x higher performance per node. As a result, the multi-threaded data node extensions not only serve to increase performance of MySQL Cluster, they also enable users to achieve significantly improved levels of utilization from current and future generations of massively multi-core, multi-thread processor designs.

    Read the article

  • Optional parameters with named query in Hibernate?

    - by Ickster
    Is there any way to specify optional parameters (such as when search parameters are provided from a form and not all parameters are required) in a named query when using Hibernate? I'm using a native SQL query, but the question is probably applicable to named HQL queries as well. I'm pretty sure the answer to this is 'no', but I haven't find the definitive answer in the documentation yet.

    Read the article

  • hierachical query to return final row

    - by jeff
    I have a hierarchical query that doesn't return an expected row (employee badge = 444). TABLE: hr_data badge fname supervisor_badge 111 Jeff 222 222 Joe 333 333 John 444 444 Tom 444 SQL: SELECT CONNECT_BY_ISCYCLE As IC, badge, fname, supervisor_badge FROM hr_data START WITH badge = '111' CONNECT BY NOCYCLE badge = PRIOR supervisor_badge What is Returned: IC badge fname supervisor_badge 0 111 Jeff 222 0 222 Joe 333 1 333 John 444 What is Expected: IC badge fname supervisor_badge 0 111 Jeff 222 0 222 Joe 333 **0** 333 John 444 **1** 444 Tom 444 How can I get this query to return the employee Tom and then stop?

    Read the article

  • Using Treelist Values to Query a Sitecore Item

    - by kirk.burleson
    I have an item named All Recipes that contains recipes named R1, R2, and R3. I have another item named My Recipes that has a treelist field named Recipes and it contains selected values R2 and R3 from the All Recipes item. The query I'm trying to write is for the Items field of an RSS Feed. What is the query syntax to show the items in All Recipes that appear in the Recipes field of My Recipes?

    Read the article

  • Problemwit sql query

    - by phenevo
    Hi, I've got query: INSERT INTO [Tasks] ([LoginName] ,[Type] ,[Filter] ,[Dictionary] ,[Description]) Select N'Anonymous',4,'SomeTable.targetcode in (select Code from cities where countrycode in ('TN')) and SomeTable.SomeValue in ('13','15')',3,N'Cities from tunis' Union All ... [Dictionary] is a part of query that i need to function on my server. I get: Incorrect syntax near ')) and SomeTable.SomeValue in (13,15)'.

    Read the article

  • MySQL query from subquery not working

    - by James Goodwin
    I am trying to return a number based on the count of results from a table and to avoid having to count the results twice in the IF statement I am using a subquery. However I get a syntax error when trying to run the query, the subquery I have tested by itself runs fine. Any ideas what is wrong with the query? The syntax looks correct to me SELECT IF(daily_count>8000,0,IF(daily_count>6000,1,2)) FROM ( SELECT count(*) as daily_count FROM orders201003 WHERE DATE_FORMAT(date_sub(curdate(), INTERVAL 1 DAY),"%d-%m-%y") = DATE_FORMAT(reqDate,"%d-%m-%y") ) q

    Read the article

  • Using Hibernate to do a query involving two tables

    - by Nathan Spears
    I'm inexperienced with sql in general, so using Hibernate is like looking for an answer before I know exactly what the question is. Please feel free to correct any misunderstandings I have. I am on a project where I have to use Hibernate. Most of what I am doing is pretty basic and I could copy and modify. Now I would like to do something different and I'm not sure how configuration and syntax need to come together. Let's say I have two tables. Table A has two (relevant) columns, user GUID and manager GUID. Obviously managers can have more than one user under them, so queries on manager can return more than one row. Additionally, a manager can be managing the same user on multiple projects, so the same user can be returned multiple times for the same manager query. Table B has two columns, user GUID and user full name. One-to-one mapping there. I want to do a query on manager GUID from Table A, group them by unique User GUID (so the same User isn't in the results twice), then return those users' full names from Table B. I could do this in sql without too much trouble but I want to use Hibernate so I don't have to parse the sql results by hand. That's one of the points of using Hibernate, isn't it? Right now I have Hibernate mappings that map each column in Table A to a field (well the get/set methods I guess) in a DAO object that I wrote just to hold that Table's data. I could also use the Hibernate DAOs I have to access each table separately and do each of the things I mentioned above in separate steps, but that would be less efficient (I assume) that doing one query. I wrote a Service object to hold the data that gets returned from the query (my example is simplified - I'm going to keep some other data from Table A and get multiple columns from Table B) but I'm at a loss for how to write a DAO that can do the join, or use the DAOs I have to do the join. FYI, here is a sample of my hibernate config file (simplified to match my example): <hibernate-mapping package="com.my.dao"> <class name="TableA" table="table_a"> <id name="pkIndex" column="pk_index" /> <property name="userGuid" column="user_guid" /> <property name="managerGuid" column="manager_guid" /> </class> </hibernate-mapping> So then I have a DAOImplementation class that does queries and returns lists like public List<TableA> findByHQL(String hql, Map<String, String> params) etc. I'm not sure how "best practice" that is either.

    Read the article

  • Issues with Rails 3.1 API with Query String to Create action on Mac OSX Mountain Lion

    - by hjaved
    Hi I've been stuck on this problem for a while and would appreciate your help. I'm writing an API to allow an external source like a Browser Query String or a smartphone to enter some model User info in a form and hit the User create action to write the data to the db. Please tell me what I'm doing wrong with the code below. I've also observed that if I have code like @user = User.new(params[:user]), that this approach only works when a user enters their data within the form. And that if I have code such as @user = User.new( name: params[:name], location: params[:location], password = params[:password], email: params[:email]), that this code ONLY works for a Query string entry, but NOT both Query string AND regular form submission. Why is that and how can I write the code above in the Users Controller Create action, so that it takes care of both situations? URL used: localhost:3000/users/create?name=John&&[email protected]&&password=secret&&location=SanFrancisco&date=06122012 The date is of type string but it doesn't show up in the database. Why? Everything else does. UsersController.rb def create @user = User.new(params[:user]) if @user.save session[:uid] = @user.id redirect_to thanks_path, notice: "Welcome #{@user.name}!" else redirect_to root_path end end New User Form: <%=u.text_field :name, placeholder: "Name"%><br> <%=u.text_field :email, placeholder: "Email"%><br> <%=u.password_field :password, placeholder: "Password"%><br> <%=u.text_field :location, placeholder: "City"%><br> <%=u.text_field :date, placeholder: "Date"%><br> <%if params[:partner_id]%> <%=u.hidden_field :partner_id, value: params[:partner_id]%> <%end%> <button class="btn btn-large btn-primary">Enter</button> I also tried to create a separate method called remotecreate for User creation for something other than a regular web form. I entered remotecreate in the Query string but it didn't work. def remotecreate @user = User.create(name: params[:name], email: params[:email], password: params[:password], location: params[:location], date: params[:date]) if @user.save session[:uid] = @user.id redirect_to thanks_path, notice: "Welcome #{@user.name}" else redirect_to root_path end end Thanks!

    Read the article

  • Convert SQL query to Ruby help

    - by Verloren
    Hey all, I need to query my database table to find which employee has the most support tickets related to them. I can do this just fine using this MySQL query: SELECT employee_id, COUNT(id) AS number_of_tickets FROM tickets GROUP BY employee_id ORDER BY number_of_tickets DESC LIMIT 1; How would write this in Ruby-on-Rails? Thanks very much for your assistance. I use Ruby version 1.8.6, Rails version 2.2.2 and MySQL Server version 5.0.

    Read the article

  • Any way to speed up this hierarchical query?

    - by RenderIn
    I've got a serious performance problem with a hierarchical query that I can't seem to fix. I am modeling several organization charts in my database, each representing a virtual organization within our company. For example, we have several temporary committees that are created from time to time and there may be a Committee Organizer role at the top of this virtual hierarchy, with several people assigned to the Committee Member role beneath the organizer. Some of our virtual organizations have many levels and several branches at each level. I have a single table in which I represent all the role assignments. i.e. a ROLE_ID column and a PARENT_ROLE_ID column which is a foreign key to the ROLE_ID column. For each assignment we also store as a column the location in the company where this person has the assignment. For example, the Committee Organizer would have a company-level/ CEO assignment, while the committee members would have department-level assignments such as ACCOUNTING, MARKETING, etc. So to model the organizer/member relationship for two individuals we would have: ROLE_ID = 4 PARENT_ROLE_ID = NULL EMPLOYEE_NUMBER = 213423 COMPANY_LOCATION = CEO ROLE_ID = 5 PARENT_ROLE_ID = 4 EMPLOYEE_NUMBER = 838221 COMPANY_LOCATION = ACCOUNTING Here's where things get tricky. I have an application that every person in the organization can log in to. When they log in they should be able to view all the virtual organizations in our company. e.g. the committee members should be able to see the committee organizer and vice-versa. However, only the committee organizer should be able to edit the committee members. The difficulty is in determining whether an individual (who can have multiple role assignments) has edit access for each other assignment. While this seems simple in the example, consider a virtual organization in which we have President at the top, 5 departments directly beneath him, 2 subdepartments below each department. We only want people in the Accounting department to be able to edit individuals in the subdepartments belonging to the Accounting department. They should not have edit access to anybody in the Marketing department or its subdepartments. To determine edit access when a user views a virtual organization in our company I run a query that executes two inline views: A) Hierarchically query for all assignments in this virtual organization and using SYS_CONNECT_BY_PATH to store the entire path to each user/role/company_location and B) Hierarchically retrieve all the assignments the individual logged in has and using the SYS_CONNECT_BY_PATH to store the entire path to each of these assignments. The result of the query is all the records from A) plus a boolean determined by joining with B) which flags whether the logged in user has edit access for each record. Indexes don't seem to be helping... it simply appears that there is too much processing going on to separate all the records and then determine edit access. One issue is that I can't store the SYS_CONNECT_BY_PATH and index it... determining whether an individual record has edit access consists of comparing if: test_record_sys_path LIKE individual_record_sys_path || '%' Is a materialized view the answer?

    Read the article

  • How to update multiple rows with one single query

    - by xRobot
    I use Postgresql + PHP. Say I have this table: Books ( id, title, year ) and this array of titles in PHP: $titles = array ("bible","kafka","Book of Eli"); now I want update all rows where the title is in the $titles array above. So I need a query like this: UPDATE books SET year = '2001-11-11' WHERE title is in $titles; Is is possible with one single query ? Or do I need to use FOR loop ?

    Read the article

  • Explicit disable MySQL query cache in some parts of program

    - by jack
    In a Django project, some cronjob programs are mainly used for administrative or analysis purposes, e.g. generating site usage stats, rotating user activities log, etc. We probably do not hope MySQL to cache queries in those programs to save memory usage and improve query cache efficiency. Is it possible to turn off MySQL query cache explicitly in those programs while keep it enabled for other parts including all views.py?

    Read the article

  • Selecting from 2 tables in a single query

    - by duder
    I have a table that I'm querying for value 43 in the second field and I return the value of the third field SELECT t1_field3 FROM table1 WHERE t1_field2=43 this returns 19, 39,73 t1_id t1_field2 t1_field3 ----- --------- --------- 1 43 19//// 2 43 39//// 3 43 73//// 4 73 43 5 13 40 Then I separately query a second table for additional information SELECT * FROM table2 WHERE t2_id=t1_field3 t2_id t2_field2 t2_field3 ----- --------- --------- 19 value19.2 value19.3 39 value39.2 value39.3 73 value73.2 value73.3 Is there a way I could combine both table1 and table2 in the same query?

    Read the article

  • What's wrong with this SQL query?

    - by ThinkingInBits
    I have two tables: photographs, and photograph_tags. Photograph_tags contains a column called photograph_id (id in photographs). You can have many tags for one photograph. I have a photograph row related to three tags: boy, stream, and water. However, running the following query returns 0 rows SELECT p.* FROM photographs p, photograph_tags c WHERE c.photograph_id = p.id AND (c.value IN ('dog', 'water', 'stream')) GROUP BY p.id HAVING COUNT( p.id )=3 Is something wrong with this query?

    Read the article

  • Linq-To-Sql equivalent for this sql query...

    - by Pandiya Chendur
    I thus far used concatenated Id string like 1,2,3 and updated in my table using this query... if exists( select ClientId from Clients where ClientId IN (SELECT i.items FROM dbo.Splitfn(@Id,',') AS i)) begin update Clients set IsDeleted=1 where ClientId IN (SELECT i.items FROM dbo.Splitfn(@Id,',') AS i) select 'deleted' as message end What is the linq-to-sql equivalent for the above query? Any suggestion...

    Read the article

  • how to pass variables this in dynamic query in sql

    - by Ranjana
    i using the dynamic query to pass the variables select a.TableName, COUNT(a.columnvalue) as '+'count'+' from Settings a where a.ColumnValue in ('+ @columnvalue +') and a.Value in (' + @value +') the @columnvalues = 'a','b','c' @value ='comm(,)','con(:)' how to pass this in dynamic query any idea???

    Read the article

  • using union in a construct sparql query

    - by simon
    hello, i have such a sparql query: select ?s ?p ?o from <http://localhost:8890/DAV/ranking> where { {<http://seekda.com/providers/cdyne.com/PhoneNotify> so:hasEndpoint ?s. ?s ?p ?o} union {<http://seekda.com/providers/cdyne.com/PhoneNotify> ?p ?o} } but i need a graph query (construct ord describe). unfortunatly i have no clue about how to use unions in construct or describe queries. please help me best regards simon

    Read the article

  • Date and time Query - problem

    - by Gold
    hi i try to run this query: select * from WorkTbl where ((Tdate = '20100414' AND Ttime = '06:00') and (Tdate <= '20100415' AND Ttime <= '06:00')) i have this date: 14/04/2010 and time: 14:00 i cant see hem, how to fix the query ? thank's in advance

    Read the article

< Previous Page | 41 42 43 44 45 46 47 48 49 50 51 52  | Next Page >