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Displaying posts with tag: Performance (reset)
Row scanned equals to 1, Is the query is optimally tuned ?

A few days ago one of our intern @mydbops reached me with a SQL query. The query scans only a row according to the execution plan. But query does not seems optimally performing.

Below is the SQL query and its explain plan. ( MySQL 5.7 )

select username, role from user_roles where username= '9977223389' ORDER BY role_id DESC LIMIT 1;

Execution plan and table structure

*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: user_roles
   partitions: NULL
         type: index
possible_keys: NULL
          key: PRIMARY
      key_len: 4
          ref: NULL
         rows: 1
     filtered: 10.00
        Extra: Using where
1 row in set, 1 warning (0.00 sec)

show create table user_roles\G
*************************** 1. row ***************************
       Table: …
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New Book: MySQL 8 Query Performance Tuning

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I have over the last few years been fortunate to have two books published through Apress, Pro MySQL NDB Cluster which I wrote together with Mikiya Okuno and MySQL Connector/Python Revealed. With the release of MySQL 8 around a year ago, I started to think of how many changes there has been in the last few MySQL versions. Since MySQL 5.6 was released as GA in early 2013, some of the major features related to performance tuning includes the Performance Schema which was greatly changed in 5.6, histograms, EXPLAIN ANALYZE, hash …

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Use Case: Continuous MySQL Operations for Growing SaaS Business

In this fourth post in our MySQL Use Case Blog Series we look at a customer of ours who was able to grow their Saas business from tens of customers initially to thousands of enterprise customers once they achieved continuous MySQL operations with Continuent Tungsten.

This particular customer, based in California, develops and sells automation software for account-based marketing as well as other marketing services and products such as SEO and content marketing. They provide solutions tailored for large enterprises and fast-growing, small businesses alike covering all industry types from technology all the way to higher education.

So how did this fast growing marketing automation SaaS provider scale from tens of customers to thousands of enterprise customers using Tungsten Clustering (currently with 600+ MySQL instances)?

The Challenge

SaaS and other web applications are inherently 24/7/365 operations, thus they …

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MySQL Group Replication and its Memory consumption (troubleshooting).

This blog is about one of the issues encountered by our Remote DBA Team in one of the production servers. We have a setup of MySQL 5.7 Single Primary (Writer) GR with cluster size of  3 . Due to OOM, the MySQL process in the primary node got killed, this repeated over the course of the time.

We all know about the OOM (out of memory), theoretically, it is a process that the Linux kernel employs when the system is critically low on memory.

In a dedicated DB server, when the OOM triggers the direct impact will be on mysqld process since it will be the most memory consuming one.

Going forward will look into the detailed analysis made to tackle the issue of OOM.

DB Environment:-

  • Service – Group Replication Cluster
  • Cluster Nodes – 3
  • GR mode – Single Primary …
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Fun with Bugs #94 - On MySQL Bug Reports I am Subscribed to, Part XXVIII

I may get a chance to speak about proper bugs processing for open source projects later this year, so I have to keep reviewing recent MySQL bugs to be ready for that. In my previous post in this series I listed some interesting MySQL bug reports created in December, 2019. Time to move on to January, 2020! Belated Happy New Year of cool MySQL Bugs!

As usual I mostly care about InnoDB, replication and optimizer bugs and explicitly mention bug reporter by name and give link to his other active reports (if any). I also pick up examples of proper (or improper) reporter and Oracle engineers attitudes. Here is the list:

  • Bug #98103 - "unexpected behavior while logging an aborted query in the slow query log".  …
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3 Step Migration of MySQL data to Clickhouse for faster analytics.

Recently one of our client approach Mydbops with Query slowness on a MySQL environment . They deployed the new code for generate the huge reports for the year end analytics data . After the deployment the queries were extremely slow and they struggled lot , then they approached us for the solution. After the analysis, their OLAP database as expected it was IO bound with 100% disk IOPS utilised during the report generation. So, the queries were starving for the Disk IO slows the process .

Problem statement :

  • Reports are majorly focused on two larger log tables ( emp_Report_model , emp_details ) .
  • The report generator (procedure) is using the count(*) statement to stimulate the aggregated data on each call. It is required for their business purpose .
  • Count(*) is terribly slow in MySQL ( Using MySQL 5.7 ) as it …
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Important Health Checks for your MySQL Master-Slave Servers

In a MySQL master-slave high availability (HA) setup, it is important to continuously monitor the health of the master and slave servers so you can detect potential issues and take corrective actions. In this blog post, we explain some basic health checks you can do on your MySQL master and slave nodes to ensure your setup is healthy. The monitoring program or script must alert the high availability framework in case any of the health checks fails, enabling the high availability framework to take corrective actions in order to ensure service availability.

MySQL Master Server Health Checks

We recommended that your MySQL master monitoring program or scripts runs at frequent intervals. Assuming that the monitoring script is running on the same server as your …

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Troubleshooting an OLAP system on InnoDB

As a part of Mydbops Consulting we have a below problem statement from one of our client.

We have a high powered server for reporting which in turn powers our internal dashboard for viewing the logistics status.Even with a high end hardware, we had a heavy CPU usage and which in turn triggers spikes in replication lag and slowness. Below is the hardware configuration.

OS : Debian 9 (Stretch)
CPU : 40
RAM : 220G (Usable)
Disk : 3T SSD with 80K sustained IOPS.
MySQL : 5.6.43-84.3-log Percona Server (GPL)
Datasize : 2.2TB

Below is the graph on CPU utilisation from Grafana.

Since the work load is purely reporting(OLAP) we could observe a similar type of queries with different ranges. Below is the Execution plan of the query. It is a join query over 6 tables.

Explain Plan:

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Faster restarts with local and partial checkpoints in MySQL NDB Cluster

The MySQL NDB Cluster team works on fundamental redesigns of core parts of NDB architecture. One of these changes is the partial checkpoint algorithm. You can now take full advantage of it when building much larger clusters: NDB 8.0 can use 16 TB data memory per data node for in-memory tables.

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Fun with Bugs #92 - On MySQL Bug Reports I am Subscribed to, Part XXVI

I'd like to continue reviewing MySQL bug reports from Community users that I considered interesting and subscribed to. Unlike in the previous post in this series, I am not going to check test cases on any competitor product, but will use only recently released MySQL 5.7.29 and 8.0.19 for checks, if any. This time I'll concentrate on bugs reported in November 2019.

As usual, I mostly care about optimizer, InnoDB and replication related bugs. Here is the list:

  • Bug #97476 - "Range optimizer skips rows". This bug reported by
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