June 19, 2013

Post: Using CHAR keys for joins, how much is the overhead ?

row in set (1.70 sec) Here is explain if someone curious, it did not really change beside key lengths: mysqlrows: 26 Extra: 2 rows in set (0.00 sec) So what about Innodb ? Innodb executed the same query in 2…. Char columns completes in 4.5 seconds on Innodb which is about 50% slower compared to …

Comment: Innodb vs MySQL index counts

column missing): > select * from test; +—-+——-+———-+ | id | data | foo | +—-+——-+———-+ | 1 | 49999 | NULL | | 2 | 1000 | some foo | +—-+——-+———-+ 2 rows in

Post: Enum Fields VS Varchar VS Int + Joined table: What is Faster?

columns. In practice you can also often use 4th variant which is not comparablerow MySQL will have to perform OS system call to read the rowrows: 225690 Extra: 2 rows in set (0.10 sec) Because we refer state by name, which is unique,it is pre-read and query

Post: Quickly finding unused indexes (and estimating their size)

….  In either case, you may want to compare or…query this view to see my indexes: mysql> select * from all_indexes limit 1 \G *************************** 1. row… 1 COLUMN_CNT: 1 COLUMN_NAMES: last_name 1 row in set …total_size / ( 1024 * 1024 ), 2) as index_size_…disk are still the same old size.  If you…

Post: The story of one MySQL Upgrade

in sync. mk-table-checksum can use replication to check consistency but comparing 2MySQL to see what is different in the tables. It turned out one of the float columns stored “-0″ in MySQLsame position again and used tcpdump and mk-query

Post: A case for MariaDB's Hash Joins

compared to doing batched index lookups (BKA). However, in Test C the cost of hash join remains the samequery would be reading 1/3 the number of rows in the table orders (left operand), and so MySQL

Post: Multi Range Read (MRR) in MySQL 5.6 and MariaDB 5.5

…the number of rows that match the condition ‘key_column=x’. You… buffer is small and there were 2 MRR range scans needed. …less the same for MariaDB 5.5 when compared to MySQL 5.5,…in-memory, in fact MRR adds extra sorting overhead which means that the queries are just a bit slower as compared to MySQL

Post: How much overhead is caused by on disk temporary tables

rows in set (0.00 sec) The table contains 1.000.000 rows with mostly unique “c” column. mysql

Post: COUNT(*) vs COUNT(col)

… | +———-+ 1 row in set (0.00 sec) mysql> select count(val) from fact; +————+ | count(val) | +————+ | 7216582 | +————+ 1 row in set (1.17 sec) mysql> select count… table MySQL has cached number of rows in this table. This is why it is able to instantly answer COUNT(*) and COUNT(val2) queriesin this case doing full table scan only if it is needed because column can be NULL. Now lets try few more queries: mysql

Post: PBXT benchmarks

2 cpu MHz : 1800.163 cache size : 1024 KB 4GB of RAM MySQL version We used MySQLcolumn is stored in key. Interesting InnoDB scalability is pretty bad for this queryrows. General notes In general PBXT looks pretty good. To be honest I did not expect such results. The one problem comparing