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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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  • project plan scheduling...

    - by Muhammad Adnan
    I am looking for some algorithm/library to get functionality like microsoft project caters for scheduling tasks dates as if we change any task date then its parent, predecessors and successors dates get effected. is there any help i can get... in any way.. Thanks,

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  • Plan Operator Tuesday round-up

    - by Rob Farley
    Eighteen posts for T-SQL Tuesday #43 this month, discussing Plan Operators. I put them together and made the following clickable plan. It’s 1000px wide, so I hope you have a monitor wide enough. Let me explain this plan for you (people’s names are the links to the articles on their blogs – the same links as in the plan above). It was clearly a SELECT statement. Wayne Sheffield (@dbawayne) wrote about that, so we start with a SELECT physical operator, leveraging the logical operator Wayne Sheffield. The SELECT operator calls the Paul White operator, discussed by Jason Brimhall (@sqlrnnr) in his post. The Paul White operator is quite remarkable, and can consume three streams of data. Let’s look at those streams. The first pulls data from a Table Scan – Boris Hristov (@borishristov)’s post – using parallel threads (Bradley Ball – @sqlballs) that pull the data eagerly through a Table Spool (Oliver Asmus – @oliverasmus). A scalar operation is also performed on it, thanks to Jeffrey Verheul (@devjef)’s Compute Scalar operator. The second stream of data applies Evil (I figured that must mean a procedural TVF, but could’ve been anything), courtesy of Jason Strate (@stratesql). It performs this Evil on the merging of parallel streams (Steve Jones – @way0utwest), which suck data out of a Switch (Paul White – @sql_kiwi). This Switch operator is consuming data from up to four lookups, thanks to Kalen Delaney (@sqlqueen), Rick Krueger (@dataogre), Mickey Stuewe (@sqlmickey) and Kathi Kellenberger (@auntkathi). Unfortunately Kathi’s name is a bit long and has been truncated, just like in real plans. The last stream performs a join of two others via a Nested Loop (Matan Yungman – @matanyungman). One pulls data from a Spool (my post – @rob_farley) populated from a Table Scan (Jon Morisi). The other applies a catchall operator (the catchall is because Tamera Clark (@tameraclark) didn’t specify any particular operator, and a catchall is what gets shown when SSMS doesn’t know what to show. Surprisingly, it’s showing the yellow one, which is about cursors. Hopefully that’s not what Tamera planned, but anyway...) to the output from an Index Seek operator (Sebastian Meine – @sqlity). Lastly, I think everyone put in 110% effort, so that’s what all the operators cost. That didn’t leave anything for me, unfortunately, but that’s okay. Also, because he decided to use the Paul White operator, Jason Brimhall gets 0%, and his 110% was given to Paul’s Switch operator post. I hope you’ve enjoyed this T-SQL Tuesday, and have learned something extra about Plan Operators. Keep your eye out for next month’s one by watching the Twitter Hashtag #tsql2sday, and why not contribute a post to the party? Big thanks to Adam Machanic as usual for starting all this. @rob_farley

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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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  • PowerShell to fetch a SQL Execution Plan

    - by Rob Farley
    With PowerShell becoming the scripting language of choice for many people, I’ve occasionally wondered about using it to analyse execution plans. After all, an execution plan is just XML, and PowerShell is just one tool which will very easily handle xml. The thing is – there’s no Get-SqlPlan cmdlet available, which has frustrated me in the past. Today I figured I’d make one. I know that I can write T-SQL to get an execution plan using SET SHOWPLAN_XML ON, but the problem is that this must be the only statement in a batch. So I used go, and a couple of newlines, and whipped up the following one-liner: function Get-SqlPlan([string] $query, [string] $server, [string] $db) { return ([xml] (invoke-sqlcmd -Server $server -Database $db -Query "set showplan_xml on;`ngo`n$query").Item( 0)) } (but please bear in mind that I have the SQL Snapins installed, which provides invoke-sqlcmd) To use this, I just do something like: $plan = get-sqlplan "select name from Production.Product" "." "AdventureWorks" And then find myself with an easy way to navigate through an execution plan! At some point I should make the function more robust, but this should be a good starter for any SQL PowerShell enthusiasts (like Aaron Nelson) out there.

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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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  • Query returns too few rows

    - by Tareq
    setup: mysql> create table product_stock( product_id integer, qty integer, branch_id integer); Query OK, 0 rows affected (0.17 sec) mysql> create table product( product_id integer, product_name varchar(255)); Query OK, 0 rows affected (0.11 sec) mysql> insert into product(product_id, product_name) values(1, 'Apsana White DX Pencil'); Query OK, 1 row affected (0.05 sec) mysql> insert into product(product_id, product_name) values(2, 'Diamond Glass Marking Pencil'); Query OK, 1 row affected (0.03 sec) mysql> insert into product(product_id, product_name) values(3, 'Apsana Black Pencil'); Query OK, 1 row affected (0.03 sec) mysql> insert into product_stock(product_id, qty, branch_id) values(1, 100, 1); Query OK, 1 row affected (0.03 sec) mysql> insert into product_stock(product_id, qty, branch_id) values(1, 50, 2); Query OK, 1 row affected (0.03 sec) mysql> insert into product_stock(product_id, qty, branch_id) values(2, 80, 1); Query OK, 1 row affected (0.03 sec) my query: mysql> SELECT IFNULL(SUM(s.qty),0) AS stock, product_name FROM product_stock s RIGHT JOIN product p ON s.product_id=p.product_id WHERE branch_id=1 GROUP BY product_name ORDER BY product_name; returns: +-------+-------------------------------+ | stock | product_name | +-------+-------------------------------+ | 100 | Apsana White DX Pencil | | 80 | Diamond Glass Marking Pencil | +-------+-------------------------------+ 1 row in set (0.00 sec) But I want to have the following result: +-------+------------------------------+ | stock | product_name | +-------+------------------------------+ | 0 | Apsana Black Pencil | | 100 | Apsana White DX Pencil | | 80 | Diamond Glass Marking Pencil | +-------+------------------------------+ To get this result what mysql query should I run?

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  • How do I filter one of the columns in a SQL Server SQL Query

    - by Kent S. Clarkson
    I have a table (that relates to a number of other tables) where I would like to filter ONE of the columns (RequesterID) - that column will be a combobox where only people that are not sales people should be selectable. Here is the "unfiltered" query, lets call it QUERY 1: SELECT RequestsID, RequesterID, ProductsID FROM dbo.Requests If using a separate query, lets call it QUERY 2, to filter RequesterID (which is a People related column, connected to People.PeopleID), it would look like this: SELECT People.PeopleID FROM People INNER JOIN Roles ON People.RolesID = Roles.RolesID INNER JOIN Requests ON People.PeopleID = Requests.RequesterID WHERE (Roles.Role <> N'SalesGuy') ORDER BY Requests.RequestsID Now, is there a way of "merging" the QUERY 2 into QUERY 1? (dbo.Requests in QUERY 1 has RequesterID populated as a Foreign Key from dbo.People, so no problem there... The connections are all right, just not know how to write the SQL query!)

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  • Best Practices of Performance Management Plan (PMP)

    - by Robert Story
    Upcoming WebcastTitle: Best Practices of Performance Management Plan (PMP)Date: April 22, 2010Time: 11 AM EST / 8 AM PST / 8.30 PM IST  Product Family: EBS HRMS SummaryThis webcast will cover the best practices of Performance Management Plan(PMP) in very common scenarios. The best practices will address major issues around plan dates, new hire, manager transfer and related events. The session will also cover HRMS Patching Strategy, Key References and various customer communication channels.A short, live demonstration (only if applicable) and question and answer period will be included.Click here to register for this session....... ....... ....... ....... ....... ....... .......The above webcast is a service of the E-Business Suite Communities in My Oracle Support.For more information on other webcasts, please reference the Oracle Advisor Webcast Schedule.Click here to visit the E-Business Communities in My Oracle Support Note that all links require access to My Oracle Support.

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  • Chrome 10 rend possible l'exécution d'applications Web en arrière plan, Google publie un exemple

    Chrome 10 rend possible l'exécution d'applications Web en arrière plan Même quand le navigateur est fermé, Google publie un exemple Mise à jour du 24/02/11 par Gordon Fowler Google vient de dévoiler une nouvelle fonctionnalité disponible dans la version 10 (en beta) de son navigateur Chrome. La fonctionnalité, baptisée « Background Pages », bien que n'ayant pas été mise en avant lors de la sortie Chrome 10, est bel et bien là. Elle permet d'exécuter des pages Web en arrière-plan de façon totalement transparente pour l'utilisateur. Certaines applications (qualifiées « d'applications d'arrière plan ») peuvent ainsi continuer à tourn...

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  • Can you recommend a good test plan template?

    - by Ethel Evans
    Can you recommend a good test plan template for an agile testing team? I know there are templates for testing on the web and have already looked at some found by search engines, but I could really use something lightweight and something that has already been tried by skilled testers and is known to work well. Many templates I've seen give me the feeling that writing test documents is expected to be a third of the work that those testers are doing, but my team really prefers to use less documentation and more actual test writing. We use a wiki for documentation, so an approach that lends itself to living documents would be great. My hope is that using a more structured approach to test planning will increase the usefulness of my test plan while reducing the effort to create it by allowing me to think about the tests, and not the format and structure of the plan. My workplace does not have something already on hand, so whatever I start doing might be adopted by the company.

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  • MySQL slow query log logging all queries

    - by Blanka
    We have a MySQL 5.1.52 Percona Server 11.6 instance that suddenly started logging every single query to the slow query log. The long_query_time configuration is set to 1, yet, suddenly we're seeing every single query (e.g. just saw one that took 0.000563s!). As a result, our log files are growing at an insane pace. We just had to truncate a 180G slow query log file. I tried setting the long_query_time variable to a really large number to see if it stopped altogether (1000000), but same result. show global variables like 'general_log%'; +------------------+--------------------------+ | Variable_name | Value | +------------------+--------------------------+ | general_log | OFF | | general_log_file | /usr2/mysql/data/db4.log | +------------------+--------------------------+ 2 rows in set (0.00 sec) show global variables like 'slow_query_log%'; +---------------------------------------+-------------------------------+ | Variable_name | Value | +---------------------------------------+-------------------------------+ | slow_query_log | ON | | slow_query_log_file | /usr2/mysql/data/db4-slow.log | | slow_query_log_microseconds_timestamp | OFF | +---------------------------------------+-------------------------------+ 3 rows in set (0.00 sec) show global variables like 'long%'; +-----------------+----------+ | Variable_name | Value | +-----------------+----------+ | long_query_time | 1.000000 | +-----------------+----------+ 1 row in set (0.00 sec)

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  • Developing an Implementation Plan with Iterations by Russ Pitts

    - by user535886
    Developing an Implementation Plan with Iterations by Russ Pitts  Ok, so you have come to grips with understanding that applying the iterative concept, as defined by OUM is simply breaking up the project effort you have estimated for each phase into one or more six week calendar duration blocks of work. Idea being the business user(s) or key recipient(s) of work product(s) being developed never go longer than six weeks without having some sort of review or prototyping of the work results for an iteration…”think-a-little”, “do-a-little”, and “show-a-little” in a six week or less timeframe…ideally the business user(s) or key recipients(s) are involved throughout. You also understand the OUM concept that you only plan for that which you have knowledge of. The concept further defined, a project plan initially is developed at a high-level, and becomes more detailed as project knowledge grows. Agreeing to this concept means you also have to admit to the fallacy that one can plan with precision beyond six weeks into a project…Anything beyond six weeks is a best guess in most cases when dealing with software implementation projects. Project planning, as defined by OUM begins with the Implementation Plan view, which is a very high-level perspective of the effort estimated for each of the five OUM phases, as well as the number of iterations within each phase. You might wonder how can you predict the number of iterations for each phase at this early point in the project. Remember project planning is not an exact science, and initially is high-level and abstract in nature, and then becomes more detailed and precise as the project proceeds. So where do you start in defining iterations for each phase for a project? The following are three easy steps to initially define the number of iterations for each phase: Step 1 => Start with identifying the known factors… …Prior to starting a project you should know: · The agreed upon time-period for an iteration (e.g 6 weeks, or 4 weeks, or…) within a phase (recommend keeping iteration time-period consistent within a phase, if not for the entire project) · The number of resources available for the project · The number of total number of man-day (effort) you have estimated for each of the five OUM phases of the project · The number of work days for a week Step 2 => Calculate the man-days of effort required for an iteration within a phase… Lets assume for the sake of this example there are 10 project resources, and you have estimated 2,536 man-days of work effort which will need to occur for the elaboration phase of the project. Let’s also assume a week for this project is defined as 5 business days, and that each iteration in the elaboration phase will last a calendar duration of 6 weeks. A simple calculation is performed to calculate the daily burn rate for a single iteration, which produces a result of… ((Number of resources * days per week) * duration of iteration) = Number of days required per iteration ((10 resources * 5 days/week) * 6 weeks) = 300 man days of effort required per iteration Step 3 => Calculate the number of iterations that can occur within a phase Next calculate the number of iterations that can occur for the amount of man-days of effort estimated for the phase being considered… (number of man-days of effort estimated / number of man-days required per iteration) = # of iterations for phase (2,536 man-days of estimated effort for phase / 300 man days of effort required per iteration) = 8.45 iterations, which should be rounded to a whole number such as 9 iterations* *Note - It is important to note this is an approximate calculation, not an exact science. This particular example is a simple one, which assumes all resources are utilized throughout the phase, including tech resources, etc. (rounding down or up to a whole number based on project factor considerations). It is also best in many cases to round up to higher number, as this provides some calendar scheduling contingency.

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  • #DAX Query Plan in SQL Server 2012 #Tabular

    - by Marco Russo (SQLBI)
    The SQL Server Profiler provides you many information regarding the internal behavior of DAX queries sent to a BISM Tabular model. Similar to MDX, also in DAX there is a Formula Engine (FE) and a Storage Engine (SE). The SE is usually handled by Vertipaq (unless you are using DirectQuery mode) and Vertipaq SE Query classes of events gives you a SQL-like syntax that represents the query sent to the storage engine. Another interesting class of events is the DAX Query Plan , which contains a couple...(read more)

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  • Career Plan: The one year plan. The three year plan.

    - by drelihan
    Hi Folks, I work as a developer however I only recently began developing full time having worked for 5 years in various roles. When it comes to career planning I think I pretty much agree with The Journeyman to Craftsman model coined in The Pragmatic Probrammer and used by Bob Martin. I see myself as a journeyman and I won't call myself a "good" (for want of a better word) until I re-evaluate my skills in 5 years time. However, as part of our careers we are encouraged to make one and three year plan with specific goals that we should hit. Unfortunately, my goal is this: Write clean code that solves a problem and is easy to maintain. From a technology point of view I want to know C++ and .net programming inside out(C#, WCF etc..) But that's it. That's my plan. Is this enough? So although there's a great discussion on what people should do with their career: http://stackoverflow.com/questions/11313/career-planning-any-tips My question is this: What's your one year plan? What's your three year plan? And am I being naive with my career? Thanks,

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  • How can I optimize this subqueried and Joined MySQL Query?

    - by kevzettler
    I'm pretty green on mysql and I need some tips on cleaning up a query. It is used in several variations through out a site. Its got some subquerys derived tables and fun going on. Heres the query: # Query_time: 2 Lock_time: 0 Rows_sent: 0 Rows_examined: 0 SELECT * FROM ( SELECT products . *, categories.category_name AS category, ( SELECT COUNT( * ) FROM distros WHERE distros.product_id = products.product_id) AS distro_count, (SELECT COUNT(*) FROM downloads WHERE downloads.product_id = products.product_id AND WEEK(downloads.date) = WEEK(curdate())) AS true_downloads, (SELECT COUNT(*) FROM views WHERE views.product_id = products.product_id AND WEEK(views.date) = WEEK(curdate())) AS true_views FROM products INNER JOIN categories ON products.category_id = categories.category_id ORDER BY created_date DESC, true_views DESC ) AS count_table WHERE count_table.distro_count > 0 AND count_table.status = 'published' AND count_table.active = 1 LIMIT 0, 8 Heres the explain: +----+--------------------+------------+-------+---------------+-------------+---------+------------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+--------------------+------------+-------+---------------+-------------+---------+------------------------------------+------+----------------------------------------------+ | 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 232 | Using where | | 2 | DERIVED | categories | index | PRIMARY | idx_name | 47 | NULL | 13 | Using index; Using temporary; Using filesort | | 2 | DERIVED | products | ref | category_id | category_id | 4 | digizald_db.categories.category_id | 9 | | | 5 | DEPENDENT SUBQUERY | views | ref | product_id | product_id | 4 | digizald_db.products.product_id | 46 | Using where | | 4 | DEPENDENT SUBQUERY | downloads | ref | product_id | product_id | 4 | digizald_db.products.product_id | 14 | Using where | | 3 | DEPENDENT SUBQUERY | distros | ref | product_id | product_id | 4 | digizald_db.products.product_id | 1 | Using index | +----+--------------------+------------+-------+---------------+-------------+---------+------------------------------------+------+----------------------------------------------+ 6 rows in set (0.04 sec) And the Tables: mysql> describe products; +---------------+--------------------------------------------------+------+-----+-------------------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------------+--------------------------------------------------+------+-----+-------------------+----------------+ | product_id | int(10) unsigned | NO | PRI | NULL | auto_increment | | product_key | char(32) | NO | | NULL | | | title | varchar(150) | NO | | NULL | | | company | varchar(150) | NO | | NULL | | | user_id | int(10) unsigned | NO | MUL | NULL | | | description | text | NO | | NULL | | | video_code | text | NO | | NULL | | | category_id | int(10) unsigned | NO | MUL | NULL | | | price | decimal(10,2) | NO | | NULL | | | quantity | int(10) unsigned | NO | | NULL | | | downloads | int(10) unsigned | NO | | NULL | | | views | int(10) unsigned | NO | | NULL | | | status | enum('pending','published','rejected','removed') | NO | | NULL | | | active | tinyint(1) | NO | | NULL | | | deleted | tinyint(1) | NO | | NULL | | | created_date | datetime | NO | | NULL | | | modified_date | timestamp | NO | | CURRENT_TIMESTAMP | | | scrape_source | varchar(215) | YES | | NULL | | +---------------+--------------------------------------------------+------+-----+-------------------+----------------+ 18 rows in set (0.00 sec) mysql> describe categories -> ; +------------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------------+------------------+------+-----+---------+----------------+ | category_id | int(10) unsigned | NO | PRI | NULL | auto_increment | | category_name | varchar(45) | NO | MUL | NULL | | | parent_id | int(10) unsigned | YES | MUL | NULL | | | category_type_id | int(10) unsigned | NO | | NULL | | +------------------+------------------+------+-----+---------+----------------+ 4 rows in set (0.00 sec) mysql> describe compatibilities -> ; +------------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------------+------------------+------+-----+---------+----------------+ | compatibility_id | int(10) unsigned | NO | PRI | NULL | auto_increment | | name | varchar(45) | NO | | NULL | | | code_name | varchar(45) | NO | | NULL | | | description | varchar(128) | NO | | NULL | | | position | int(10) unsigned | NO | | NULL | | +------------------+------------------+------+-----+---------+----------------+ 5 rows in set (0.01 sec) mysql> describe distros -> ; +------------------+--------------------------------------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------------+--------------------------------------------------+------+-----+---------+----------------+ | id | int(10) unsigned | NO | PRI | NULL | auto_increment | | product_id | int(10) unsigned | NO | MUL | NULL | | | compatibility_id | int(10) unsigned | NO | MUL | NULL | | | user_id | int(10) unsigned | NO | | NULL | | | status | enum('pending','published','rejected','removed') | NO | | NULL | | | distro_type | enum('file','url') | NO | | NULL | | | version | varchar(150) | NO | | NULL | | | filename | varchar(50) | YES | | NULL | | | url | varchar(250) | YES | | NULL | | | virus | enum('READY','PASS','FAIL') | YES | | NULL | | | downloads | int(10) unsigned | NO | | 0 | | +------------------+--------------------------------------------------+------+-----+---------+----------------+ 11 rows in set (0.01 sec) mysql> describe downloads; +------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------+------------------+------+-----+---------+----------------+ | id | int(10) unsigned | NO | PRI | NULL | auto_increment | | product_id | int(10) unsigned | NO | MUL | NULL | | | distro_id | int(10) unsigned | NO | MUL | NULL | | | user_id | int(10) unsigned | NO | MUL | NULL | | | ip_address | varchar(15) | NO | | NULL | | | date | datetime | NO | | NULL | | +------------+------------------+------+-----+---------+----------------+ 6 rows in set (0.01 sec) mysql> describe views -> ; +------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------+------------------+------+-----+---------+----------------+ | id | int(10) unsigned | NO | PRI | NULL | auto_increment | | product_id | int(10) unsigned | NO | MUL | NULL | | | user_id | int(10) unsigned | NO | MUL | NULL | | | ip_address | varchar(15) | NO | | NULL | | | date | datetime | NO | | NULL | | +------------+------------------+------+-----+---------+----------------+ 5 rows in set (0.00 sec)

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  • SQL query: Delete a entry which is not present in a join table?

    - by Mestika
    Hi, I’m going to delete all users which has no subscription but I seem to run into problems each time I try to detect the users. My schemas look like this: Users = {userid, name} Subscriptionoffering = {userid, subscriptionname} Now, what I’m going to do is to delete all users in the user table there has a count of zero in the subscriptionoffering table. Or said in other words: All users which userid is not present in the subscriptionoffering table. I’ve tried with different queries but with no result. I’ve tried to say where user.userid <> subscriptionoffering.userid, but that doesn’t seem to work. Do anyone know how to create the correct query? Thanks Mestika

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  • Using SQL Sentry Plan Explorer

    - by fatherjack
    LiveJournal Tags: How To,SSMS,Tips and tricks,Execution Plans This is a quick tip that I hope will help you use SQL Sentry's Plan Explorer tool. It's a really great tool for viewing Execution Plans - something that SSMS isn't too great at. If you don't have the tool then you can download it for free from http://www.sqlsentry.net/plan-explorer/sql-server-query-view.asp. So, just a little setup is required before I can show you the tip in full. Create a directory on your Desktop called Execution...(read more)

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  • Execution plan warnings–The final chapter

    - by Dave Ballantyne
    In my previous posts (here and here), I showed examples of some of the execution plan warnings that have been added to SQL Server 2012.  There is one other warning that is of interest to me : “Unmatched Indexes”. Firstly, how do I know this is the final one ?  The plan is an XML document, right ? So that means that it can have an accompanying XSD.  As an XSD is a schema definition, we can poke around inside it to find interesting things that *could* be in the final XML file. The showplan schema is stored in the folder Microsoft SQL Server\110\Tools\Binn\schemas\sqlserver\2004\07\showplan and by comparing schemas over releases you can get a really good idea of any new functionality that has been added. Here is the section of the Sql Server 2012 showplan schema that has been interesting me so far : <xsd:complexType name="AffectingConvertWarningType"> <xsd:annotation> <xsd:documentation>Warning information for plan-affecting type conversion</xsd:documentation> </xsd:annotation> <xsd:sequence> <!-- Additional information may go here when available --> </xsd:sequence> <xsd:attribute name="ConvertIssue" use="required"> <xsd:simpleType> <xsd:restriction base="xsd:string"> <xsd:enumeration value="Cardinality Estimate" /> <xsd:enumeration value="Seek Plan" /> <!-- to be extended here --> </xsd:restriction> </xsd:simpleType> </xsd:attribute> <xsd:attribute name="Expression" type ="xsd:string" use="required" /></xsd:complexType><xsd:complexType name="WarningsType"> <xsd:annotation> <xsd:documentation>List of all possible iterator or query specific warnings (e.g. hash spilling, no join predicate)</xsd:documentation> </xsd:annotation> <xsd:choice minOccurs="1" maxOccurs="unbounded"> <xsd:element name="ColumnsWithNoStatistics" type="shp:ColumnReferenceListType" minOccurs="0" maxOccurs="1" /> <xsd:element name="SpillToTempDb" type="shp:SpillToTempDbType" minOccurs="0" maxOccurs="unbounded" /> <xsd:element name="Wait" type="shp:WaitWarningType" minOccurs="0" maxOccurs="unbounded" /> <xsd:element name="PlanAffectingConvert" type="shp:AffectingConvertWarningType" minOccurs="0" maxOccurs="unbounded" /> </xsd:choice> <xsd:attribute name="NoJoinPredicate" type="xsd:boolean" use="optional" /> <xsd:attribute name="SpatialGuess" type="xsd:boolean" use="optional" /> <xsd:attribute name="UnmatchedIndexes" type="xsd:boolean" use="optional" /> <xsd:attribute name="FullUpdateForOnlineIndexBuild" type="xsd:boolean" use="optional" /></xsd:complexType> I especially like the “to be extended here” comment,  high hopes that we will see more of these in the future.   So “Unmatched Indexes” was a warning that I couldn’t get and many thanks must go to Fabiano Amorim (b|t) for showing me the way.   Filtered indexes were introduced in Sql Server 2008 and are really useful if you only need to index only a portion of the data within a table.  However,  if your SQL code uses a variable as a predicate on the filtered data that matches the filtered condition, then the filtered index cannot be used as, naturally,  the value in the variable may ( and probably will ) change and therefore will need to read data outside the index.  As an aside,  you could use option(recompile) here , in which case the optimizer will build a plan specific to the variable values and use the filtered index,  but that can bring about other problems.   To demonstrate this warning, we need to generate some test data :   DROP TABLE #TestTab1GOCREATE TABLE #TestTab1 (Col1 Int not null, Col2 Char(7500) not null, Quantity Int not null)GOINSERT INTO #TestTab1 VALUES (1,1,1),(1,2,5),(1,2,10),(1,3,20), (2,1,101),(2,2,105),(2,2,110),(2,3,120)GO and then add a filtered index CREATE INDEX ixFilter ON #TestTab1 (Col1)WHERE Quantity = 122 Now if we execute SELECT COUNT(*) FROM #TestTab1 WHERE Quantity = 122 We will see the filtered index being scanned But if we parameterize the query DECLARE @i INT = 122SELECT COUNT(*) FROM #TestTab1 WHERE Quantity = @i The plan is very different a table scan, as the value of the variable used in the predicate can change at run time, and also we see the familiar warning triangle. If we now look at the properties pane, we will see two pieces of information “Warnings” and “UnmatchedIndexes”. So, handily, we are being told which filtered index is not being used due to parameterization.

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  • What is an “implementation plan”?

    - by Abe Miessler
    I was recently given the task of creating an implementation plan document. When I asked for an example of one that I could look at, I was told to look at the Project Plan that had already been created an use that as a base. I'm still a bit confused on what I should be creating. Can anyone point me to a good example out there or to something that explains what this is and more importantly the details about what it should contain.

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  • Developing a Support Plan for Cloud Applications

    - by BuckWoody
    Last week I blogged about developing a High-Availability plan. The specifics of a given plan aren't as simple as "Step 1, then Step 2" because in a hybrid environment (which most of us have) the situation changes the requirements. There are those that look for simple "template" solutions, but unless you settle on a single vendor and a single way of doing things, that's not really viable. The same holds true for support. As I've mentioned before, I'm not fond of the term "cloud", and would rather use the tem "Distributed Computing". That being said, more people understand the former, so I'll just use that for now. What I mean by Distributed Computing is leveraging another system or setup to perform all or some of a computing function. If this definition holds true, then you're essentially creating a partnership with a vendor to run some of your IT - whether that be IaaS, PaaS or SaaS, or more often, a mix. In your on-premises systems, you're the first and sometimes only line of support. That changes when you bring in a Cloud vendor. For Windows Azure, we have plans for support that you can pay for if you like. http://www.windowsazure.com/en-us/support/plans/ You're not off the hook entirely, however. You still need to create a plan to support your users in their applications, especially for the parts you control. The last thing they want to hear is "That's vendor X's problem - you'll have to call them." I find that this is often the last thing the architects think about in a solution. It's fine to put off the support question prior to deployment, but I would hold off on calling it "production" until you have that plan in place. There are lots of examples, like this one: http://www.va-interactive.com/inbusiness/editorial/sales/ibt/customer.html some of which are technology-specific. Once again, this is an "it depends" kind of approach. While it would be nice if there was just something in a box we could buy, it just doesn't work that way in a hybrid system. You have to know your options and apply them appropriately.

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  • Developing a Support Plan for Cloud Applications

    - by BuckWoody
    Last week I blogged about developing a High-Availability plan. The specifics of a given plan aren't as simple as "Step 1, then Step 2" because in a hybrid environment (which most of us have) the situation changes the requirements. There are those that look for simple "template" solutions, but unless you settle on a single vendor and a single way of doing things, that's not really viable. The same holds true for support. As I've mentioned before, I'm not fond of the term "cloud", and would rather use the tem "Distributed Computing". That being said, more people understand the former, so I'll just use that for now. What I mean by Distributed Computing is leveraging another system or setup to perform all or some of a computing function. If this definition holds true, then you're essentially creating a partnership with a vendor to run some of your IT - whether that be IaaS, PaaS or SaaS, or more often, a mix. In your on-premises systems, you're the first and sometimes only line of support. That changes when you bring in a Cloud vendor. For Windows Azure, we have plans for support that you can pay for if you like. http://www.windowsazure.com/en-us/support/plans/ You're not off the hook entirely, however. You still need to create a plan to support your users in their applications, especially for the parts you control. The last thing they want to hear is "That's vendor X's problem - you'll have to call them." I find that this is often the last thing the architects think about in a solution. It's fine to put off the support question prior to deployment, but I would hold off on calling it "production" until you have that plan in place. There are lots of examples, like this one: http://www.va-interactive.com/inbusiness/editorial/sales/ibt/customer.html some of which are technology-specific. Once again, this is an "it depends" kind of approach. While it would be nice if there was just something in a box we could buy, it just doesn't work that way in a hybrid system. You have to know your options and apply them appropriately.

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