Search Results for: how search data from two different table in mysql query

MySQL 5.6 vs MySQL 5.5 and the Star Schema Benchmark

So far most of the benchmarks posted about MySQL 5.6 use the sysbench OLTP workload.  I wanted to test a set of queries which, unlike sysbench, utilize joins.  I also wanted an easily reproducible set of data which is more rich than the simple sysbench table.  The Star Schema Benchmark (SSB) seems ideal for this. […]

InnoDB Full-text Search in MySQL 5.6: Part 2, The Queries!

This is part 2 in a 3 part series. In part 1, we took a quick look at some initial configuration of InnoDB full-text search and discovered a little bit of quirky behavior; here, we are going to run some queries and compare the result sets. Our hope is that the one of two things […]

The Optimization That (Often) Isn’t: Index Merge Intersection

Prior to version 5.0, MySQL could only use one index per table in a given query without any exceptions; folks that didn’t understand this limitation would often have tables with lots of single-column indexes on columns which commonly appeared in their WHERE clauses, and they’d wonder why the EXPLAIN plan for a given SELECT would […]

Recovery after DROP & CREATE

In a very popular data loss scenario a table is dropped and empty one is created with the same name. This is because  mysqldump in many cases generates the “DROP TABLE” instruction before the “CREATE TABLE”:

If there were no subsequent CREATE TABLE the recovery would be trivial. Index_id of the PRIMARY index of […]

How To Test Your Upgrades – pt-upgrade

Upgrades are usually one of the biggest part of any database infrastructure maintenance. Even with enough planning something else can go bad after sending your production application to the version you’ve upgraded to. Let’s look at how one Percona Toolkit tool, pt-upgrade can help you identify what to expect and test your upgrades better which […]

The case for getting rid of duplicate “sets”

The most useful feature of the relational database is that it allows us to easily process data in sets, which can be much faster than processing it serially. When the relational database was first implemented, write-ahead-logging and other technologies did not exist. This made it difficult to implement the database in a way that matched […]