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Search Results for: mysql compression index

Find unused indexes on MongoDB and TokuMX

Finding and removing unused indexes is a pretty common technique to improve overall performance of relational databases. Less indexes means faster insert and updates but also less disk space used. The usual way to do …

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MySQL is crashing: a support engineer’s point of view

In MySQL QA Episode #12, “MySQL is Crashing, now what?,” Roel demonstrated how to collect crash-related information that will help Percona discover what the issue is that you are experiencing, and fix it. As a Support …

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Deep dive into MySQL’s innochecksum tool

One of our Percona Support customers recently reported that Percona XtraBackup failed with a page corruption error on an InnoDB table. The customer thought it was a problem or bug in the Percona XtraBackup tool. …

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MySQL compression: Compressed and Uncompressed data size

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 …

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A closer look at the MySQL ibdata1 disk space issue and big tables

A recurring and very common customer issue seen here at the Percona Support team involves how to make the ibdata1 file “shrink” within MySQL. I can only imagine there’s a degree of regret by some of …

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Getting to know TokuDB for MySQL

During last April’s Percona Live MySQL Conference and Expo, TokuDB celebrated it’s first full-year as an open source storage engine. I still remember reading the official announcement and the expectations it created one year ago. The …

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Using InfiniDB MySQL server with Hadoop cluster for data analytics

In my previous post about Hadoop and Impala I benchmarked performance of analytical queries in Impala. This time I’ve tried InfiniDB for Hadoop (open-source version) on the modern hardware with an 8-node Hadoop cluster. One of the main advantages (at …

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Using Apache Hadoop and Impala together with MySQL for data analysis

Apache Hadoop is commonly used for data analysis. It is fast for data loads and scalable. In a previous post I showed how to integrate MySQL with Hadoop. In this post I will show how …

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March 20 Webinar: How to Scale MySQL for Big Data Applications

You may think that you have to buy, install, and get up to speed on a new database if you want to work with large amounts of data, but you can do more than you …

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The MySQL ARCHIVE storage engine – Alternatives

In my previous post I pointed out that the existing ARCHIVE storage engine in MySQL may not be the one that will satisfy your needs when it comes to effectively storing large and/or old data. But …

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