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Displaying posts with tag: mysql (reset)

Page read performance: MySQL 5.7 vs previous releases
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For this test I used sysbench to determine the peak rate for disk reads per second from InnoDB with fast storage. Fast storage in this case is the OS filesystem cache. I want to know the peak for MySQL 5.7.5 and whether there is a regression from 5.6. My summary is:
  • 5.7.5 is 12% to 15% worse than 5.6.21 at 1 thread. I hope we can fix this via bug 74342.
  • 5.7.5 is 2% to 4% worse than 5.6.21 at 8, 16 and 32 threads
  • 5.6/5.7 are much better than 5.0 especially at high concurrency
  • Page size (16k, 8k, 4k) has a big impact on the peak only when compression is used. 
setup

The test server has 40 hyperthread cores and is shared by the sysbench client and mysqld server.

I used my sysbench 0.4




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How To Run Basic Queries of MySQL / MariaDB on Fedora 20 For Newbies !!
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Following Article Describes How To Perform Most Basic MYSQL / MariaDB Queries on Fedora 20? or How to Run MySQL on Fedora 20 ? Which is Latest Version of Linux Based Operating System Project. Last Operation of This Assignment also describes How to change MySQL 'Root' User password on Linux.
It is also a part of 3rd Year, 5th sem Computer Engineering Academic Curriculum of Pune University. As PL 1 Subject. Group A, Assignment 1. It's Problem Statement And Solution is Given Below. You may also Checkout Database Management System complete syllabus & Tutorial of 5th sem subject called Database Management systems application.

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High-Availability at MySQL Central
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This year’s MySQL Central at Oracle Open World was an exhilarating experience. In contrast to the previous year’s MySQL Connect events, MySQL have now got their own Central at the main Oracle Open World. In the previous years, we were always short on time and trying to get a lot of sessions into just two days was just to much. This time I could both present sessions, attend sessions by other users, and also to talk to people in the MySQL community: something that I really enjoy and also find very valuable to see where we should be heading.

This year, the “MySQL Fabric Team” representation on MySQL Central was me and Narayanan Venkateswaran, which is heading the sharding solution in MySQL Fabric. Together with the conference, we also released MySQL Fabric 1.5.2 as the GA release of MySQL Fabric 1.5 containing

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MariaDB 10.1: Better query optimization for ORDER BY … LIMIT
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For some reason, we’ve been getting a lot of issues with ORDER BY optimization recently. The fixes have passed Elena Stepanova’s scrutiny and I’ve pushed them to MariaDB 10.1. Now, MariaDB’s ORDER BY ... LIMIT optimizer:

  • Doesn’t make stupid choices when several multi-part keys and potential range accesses are present (MDEV-6402)
  • Always uses “range” and (not full “index” scan) when it switches to an index to satisfy ORDER BY … LIMIT (MDEV-6657)
  • Tries hard to be smart and use cost/number of records estimates from other parts of the optimizer (MDEV-6384, MDEV-465, MySQL
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MariaDB 5.5.40 Overview and Highlights
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MariaDB 5.5.40 was recently released (it is the latest MariaDB 5.5), and is available for download here:

https://downloads.mariadb.org/mariadb/5.5.40/

This is a maintenance release, and so there are not too many big changes of note, just a number of normal bug fixes. However, there are a few items worth mentioning:

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A discovery - Index Condition Pushdown can cause a slowdown after all
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MariaDB 5.5 and then MySQL 5.6 got Index Condition Pushdown (ICP) optimization (initially coded by yours truly). The idea of ICP is simple: after reading the index record, check the part of WHERE condition that can be computed using index columns, and only then read the table record. That way, we avoid reading table rows that don’t satisfy index condition:

It seems apparent that ICP can never make things slower. The WHERE clause has to be checked anyway, and not reading certain records can only make things faster.

That was what I thought, too, until recently Joffrey Michaie observed the contrary “in the wild”: we’ve got a real-world case where

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Creating PivotTables when importing MySQL data using MySQL for Excel
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In a previous blog post (Importing related MySQL tables into an Excel Data Model using MySQL for Excel) we covered in detail how an Excel Data Model can be created containing tables and their relationships so the data can be analyzed in Excel via a PivotTable. In this blog post we are going to talk about one of the features included since MySQL for Excel 1.3.0 that allows you to create PivotTables for data imported from MySQL tables, views or stored procedures, or more importantly for the whole Excel Data Model if it is created.

Remember you can install the latest GA or maintenance version using the MySQL Installer or optionally you can download directly any GA or non-GA version from the MySQL Developer Zone.

Low-concurrency performance for updates with InnoDB: MySQL 5.7 vs previous releases
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First I tested updates with the Heap engine as a base case and now I report on InnoDB to find regressions that are specific to it. The workload is described in the previous blog post. Response time is measured at 1, 4 and 32 threads for two types of updates. The unindexed update increments an unindexed column. The indexed update updates a column that is in a secondary index. Tests are run with the binlog enabled and disabled. Tests are done for MySQL versions 5.0.85, 5.1.63, 5.5.40, 5.6.21 and 5.7.5. In some cases tests are also done with the adaptive hash index disabled. The test database has 64,000 rows but all updates are to one row (lots of contention). The client is mysqlslap running on the same host as mysqld. The test server has 40 hyperthread  [Read more...]
MySQL compression: Compressed and Uncompressed data size
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MySQL has information_schema.tables that contain information such as “data_length” or “avg_row_length.” Documentation on this table however is quite poor, making an assumption that those fields are self explanatory – they are not when it comes to tables that employ compression. And this is where inconsistency is born. Lets take a look at the same table containing some highly compressible data using different storage engines that support MySQL compression:

TokuDB:

mysql> select * from information_schema.tables where table_schema='test' G
*************************** 1. row ***************************
TABLE_CATALOG: def
TABLE_SCHEMA: test
TABLE_NAME: comp
TABLE_TYPE: BASE TABLE
ENGINE: TokuDB
VERSION: 10
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Low-concurrency performance for updates and the Heap engine: MySQL 5.7 vs previous releases
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The low-concurrency performance regression evaluation continues after evaluating range queries. This post covers updates with the Heap engine. The Heap engine is used as the base case and the next post has results for InnoDB. The database has 64,000 rows but all updates were for the same row. Tests were done for updates to an indexed and then an unindexed column at 1, 4 and 32 threads. Tests were also repeated with the binlog disabled and then enabled. There are regressions at 1, 4 and 32 threads. The summary is:
  • Response time at 1 thread for 5.7.5 is between 1.55X and 1.67X worse than 5.0.85 
  • Response time at 32 threads for 5.7.5 is between 1.19X and 1.49X worse than 5.0.85 
  • In all cases it is worse in 5.7 than in

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10 Newer Entries Showing entries 31 to 40 of 16444 10 Older Entries

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