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Displaying posts with tag: RocksDB (reset)
Percona Server for MySQL 5.7.22-22 Is Now Available

Percona announces the GA release of Percona Server for MySQL 5.7.22-22 on on May 31, 2018. Download the latest version from the Percona web site or the Percona Software Repositories. You can also run Docker containers from the images in the Docker Hub repository.

Based on MySQL 5.7.22, including all the bug fixes in it, Percona Server for MySQL 5.7.22-22 is the current GA release in the Percona Server for MySQL 5.7 series. Percona …

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Percona Server for MySQL 5.7.21-21 Is Now Available with Increased Built-In Security Enhancements

Percona announces the GA release of Percona Server for MySQL 5.7.21-21 on on April 24, 2018. Download the latest version from the Percona web site or the Percona Software Repositories. You can also run Docker containers from the images in the Docker Hub repository.

This version of Percona Server for MySQL 5.7.21 includes three new encryption features – Vault keyring plug-in, encryption for InnoDB general tablespaces, and encryption for binary log files.

These new capabilities, which allow companies to immediately …

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Index Structures, Access Methods, whatever

I prefer to use Index Structures when writing about algorithms for indexing data stored on disk and SSD but Access Methods is another popular name. Recently I have been working on a high-level comparison (lots of hand waving) of index structures in terms of read, write, space and cache amplification.

I started by dividing the index structures into tree-based and hash-based. Tree-based support range queries while hash-based do not. Most of my experience is with tree-based approaches. There was a lot of research on hash-based in the 80s (extendible, dynamic and linear hashing), they are in production today but not as prominent as b-trees, and there is recent research on them. This paper by Seltzer and Yigit is a great overview on hash-based index …

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Cache amplification

How much of the database must be in cache so that a point-query does at most one read from storage? I call this cache-amplification or cache amplification. The answer depends on the index structure (b-tree, LSM, something else). Cache amplification can join read, write and space amplification. Given that RWS was renamed RUM by the excellent RUM Conjecture now we have CRUM which is close to crummy. I briefly wrote about this in a previous post.

To do at most 1 storage read for a point query:

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Percona Server for MySQL 5.7.21-20 Is Now Available

Percona announces the GA release of Percona Server for MySQL 5.7.21-20 on February 19, 2018. Download the latest version from the Percona web site or the Percona Software Repositories. You can also run Docker containers from the images in the Docker Hub repository.

Based on MySQL 5.7.21, including all the bug fixes in it, Percona Server for MySQL 5.7.21-20 is the current GA release in the Percona Server for MySQL 5.7 series. Percona …

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MyRocks Engine: Things to Know Before You Start

Percona recently released Percona Server with MyRocks as GA. You can see how Facebook explains wins they see in production with MyRocks. Now if you use Percona repositories, you can simply install MyRocks plugin and enable it with ps-admin --enable-rocksdb.

There are some major and minor differences when comparing it to typical InnoDB deployments, and I want to highlight them here. The first important difference is that MyRocks (based on RocksDB) uses  …

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Percona Server for MySQL 5.7.20-19 Is Now Available

Percona announces the GA release of Percona Server for MySQL 5.7.20-19 on January 3, 2018. Download the latest version from the Percona web site or the Percona Software Repositories. You can also run Docker containers from the images in the Docker Hub repository.

Based on MySQL 5.7.20, including all the bug fixes in it, Percona Server for MySQL 5.7.20-19 is the current GA release in the Percona Server for MySQL 5.7 series. …

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MyRocks, InnoDB and TokuDB: a summary

This has links to all performance reports from my recent series. I wanted to publish all of this by year end because I am taking a break from running and documenting MyRocks and MongoRocks performance.

Small server

Results from Intel NUC servers I have at home.

Insert benchmark:

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Sysbench: IO-bound and a fast server, part 2

This post has results for sysbench with an IO-bound workload and a fast server. It uses 1 table with 800M rows. The previous post had results for 8 tables with 100M rows/table. The goal is to understand the impact from more contention. Before that I published a report comparing sysbench with 8 tables vs 1 table for an in-memory workload.

All of the data is on github. With the exception of the scan section, the graphs below have the absolute QPS for 48 concurrent clients using 8 tables and 1 table.

tl;dr

  • MyRocks scans are up to 2X faster with readahead
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Sysbench: IO-bound and a fast server

In this post I share results for IO-bound sysbench on a fast server using MyRocks, InnoDB and TokuDB.

tl;dr

  • MyRocks is more space efficient than InnoDB. InnoDB uses ~2.2X more space than compressed MyRocks and ~1.1X more space than uncompressed MyRocks.
  • MyRocks is more write effcient than InnoDB. InnoDB writes ~7.9X more to storage per update than MyRocks on the update-index test.
  • For full index scans InnoDB 5.6 is ~2X faster than MyRocks. But with readahead enabled, uncompressed MyRocks is ~2X faster than InnoDB 5.6 and comparable to InnoDB 5.7/8.0.
  • MyRocks is >= InnoDB 5.7/8.0 for 3 of the four update-only tests. update-one is the only test on which it isn't similar or better and that test has a cached working set.
  • MyRocks is similar to InnoDB 5.6 on the insert only test.
  • MyRocks matches InnoDB 5.7/8.0 for read-write with range-size=100 (the …
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