Monthly Archives - January 2016

Bare-metal servers for button-push database-as-a-service

Enterprises’ demand flexibility, scalability and efficiency to keep up with the demands of their customers — while maintaining the bottom line. To solve this, they’re running to cloud infrastructure services to both cut costs and take advantage of cutting-edge technology innovations. Clouds have brought simplicity and ease of use to infrastructure management. However, with […]

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MongoDB revs you up: What storage engine is right for you? (Part 2)

Differentiating Between MongoDB Storage Engines: WiredTiger
In our last post, we discussed what a storage engine is, and how you can determine the characteristics of one versus the other. From that post:
“A database storage engine is the underlying software that a DBMS uses to create, read, update and delete data from a database. The storage […]

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Percona XtraDB Cluster 5.6.27-25.13 is now available

How to calculate the correct size of Percona XtraDB Cluster's gcache

Percona is glad to announce the new release of Percona XtraDB Cluster 5.6 on January 11, 2016. Binaries are available from the downloads area or from our software repositories.
Percona XtraDB Cluster 5.6.27-25.13 is now the current release, based on the following:

Percona Server 5.6.27-75.0
Percona Server 5.6.27-76.0
Galera Replicator 3.13
Codership wsrep API 25.12

All of Percona software is open-source […]

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ordering_operation: EXPLAIN FORMAT=JSON knows everything about ORDER BY processing

EXPLAIN FORMAT=JSON

We’ve already discussed using the ORDER BY clause with subqueries. You can also, however, use the 
ORDER BY clause with sorting results of one of the columns. Actually, this is most common way to use this clause.
Sometimes such queries require using temporary tables or filesort, and a regular
EXPLAIN  clause provides this information. But it doesn’t show if […]

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Apache Spark with Air ontime performance data

There is a growing interest in Apache Spark, so I wanted to play with it (especially after Alexander Rubin’s Using Apache Spark post).
To start, I used the recently released Apache Spark 1.6.0 for this experiment, and I will play with “Airlines On-Time Performance” database from
http://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236&DB_Short_Name=On-Time. You can find the scripts I used here https://github.com/Percona-Lab/ontime-airline-performance. The uncompressed dataset is about 70GB, which is not […]

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MongoDB revs you up: What storage engine is right for you? (Part 1)

Differentiating Between MongoDB Storage Engines
The tremendous data growth of the last decade has affected almost all aspects of applications and application use. Since nearly all applications interact with a database at some point, this means databases needed to adapt to the change in usage conditions as well. Database technology has grown significantly in the last […]

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grouping_operation, duplicates_removal: EXPLAIN FORMAT=JSON has all details about GROUP BY

In the previous EXPLAIN FORMAT=JSON is Cool! series blog post, we discussed the  
group_by_subqueries  member (which is child of
grouping_operation). Let’s now focus on the 
grouping_operation  and other details of 
GROUP BY  processing.

grouping_operation simply shows the details of what happens when the 
GROUP BY clause is run:

MySQL

mysql> explain format=json select dept_no from dept_emp group by dept_noG
*************************** 1. row ***************************
EXPLAIN: {
[…]

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