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mysql_utils
Python2016–2016
pinterest / mysql_utils · Archived

mysql_utils

Pinterest MySQL Management Tools

2Distinct people
2Mentions
0Explicit recommenders
876GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Pinterest MySQL Management Tools

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:03:16 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by 6-hour interval2 dated mentions

Observed mentions: 2016-08-12 20:41:59 UTC to 2016-08-18 17:22:13 UTC.

012016-08-12 18:00:00 UTC to 2016-08-13 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsAug 12, 18:002016-08-13 00:00:00 UTC to 2016-08-13 06:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-13 06:00:00 UTC to 2016-08-13 12:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-13 12:00:00 UTC to 2016-08-13 18:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-13 18:00:00 UTC to 2016-08-14 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-14 00:00:00 UTC to 2016-08-14 06:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-14 06:00:00 UTC to 2016-08-14 12:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-14 12:00:00 UTC to 2016-08-14 18:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-14 18:00:00 UTC to 2016-08-15 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-15 00:00:00 UTC to 2016-08-15 06:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-15 06:00:00 UTC to 2016-08-15 12:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-15 12:00:00 UTC to 2016-08-15 18:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsAug 15, 12:002016-08-15 18:00:00 UTC to 2016-08-16 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-16 00:00:00 UTC to 2016-08-16 06:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-16 06:00:00 UTC to 2016-08-16 12:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-16 12:00:00 UTC to 2016-08-16 18:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-16 18:00:00 UTC to 2016-08-17 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-17 00:00:00 UTC to 2016-08-17 06:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-17 06:00:00 UTC to 2016-08-17 12:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-17 12:00:00 UTC to 2016-08-17 18:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-17 18:00:00 UTC to 2016-08-18 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-18 00:00:00 UTC to 2016-08-18 06:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-18 06:00:00 UTC to 2016-08-18 12:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-18 12:00:00 UTC to 2016-08-18 18:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsAug 18, 12:00

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Aug 12, 18:002016-08-12 18:00:00 UTC2016-08-13 00:00:00 UTC101
Aug 13, 00:002016-08-13 00:00:00 UTC2016-08-13 06:00:00 UTC000
Aug 13, 06:002016-08-13 06:00:00 UTC2016-08-13 12:00:00 UTC000
Aug 13, 12:002016-08-13 12:00:00 UTC2016-08-13 18:00:00 UTC000
Aug 13, 18:002016-08-13 18:00:00 UTC2016-08-14 00:00:00 UTC000
Aug 14, 00:002016-08-14 00:00:00 UTC2016-08-14 06:00:00 UTC000
Aug 14, 06:002016-08-14 06:00:00 UTC2016-08-14 12:00:00 UTC000
Aug 14, 12:002016-08-14 12:00:00 UTC2016-08-14 18:00:00 UTC000
Aug 14, 18:002016-08-14 18:00:00 UTC2016-08-15 00:00:00 UTC000
Aug 15, 00:002016-08-15 00:00:00 UTC2016-08-15 06:00:00 UTC000
Aug 15, 06:002016-08-15 06:00:00 UTC2016-08-15 12:00:00 UTC000
Aug 15, 12:002016-08-15 12:00:00 UTC2016-08-15 18:00:00 UTC000
Aug 15, 18:002016-08-15 18:00:00 UTC2016-08-16 00:00:00 UTC000
Aug 16, 00:002016-08-16 00:00:00 UTC2016-08-16 06:00:00 UTC000
Aug 16, 06:002016-08-16 06:00:00 UTC2016-08-16 12:00:00 UTC000
Aug 16, 12:002016-08-16 12:00:00 UTC2016-08-16 18:00:00 UTC000
Aug 16, 18:002016-08-16 18:00:00 UTC2016-08-17 00:00:00 UTC000
Aug 17, 00:002016-08-17 00:00:00 UTC2016-08-17 06:00:00 UTC000
Aug 17, 06:002016-08-17 06:00:00 UTC2016-08-17 12:00:00 UTC000
Aug 17, 12:002016-08-17 12:00:00 UTC2016-08-17 18:00:00 UTC000
Aug 17, 18:002016-08-17 18:00:00 UTC2016-08-18 00:00:00 UTC000
Aug 18, 00:002016-08-18 00:00:00 UTC2016-08-18 06:00:00 UTC000
Aug 18, 06:002016-08-18 06:00:00 UTC2016-08-18 12:00:00 UTC000
Aug 18, 12:002016-08-18 12:00:00 UTC2016-08-18 18:00:00 UTC110

What Hacker News says

2 sources
Hi cookiecaper, All our operational code (other than pinterest specific bits) is open sourced https://github.com/pinterest/mysql_utils Both statement and row based replication can be very reliable in modern versions of MySQL. It is my experience the ways data is corrupted are: 1. read_only not being set on slaves, so random users can write to the slave. We set read_only on startup based on service discovery. 2. Bad automation for failovers. See https://github.com/pinterest/mysql_utils/blob/master/mysql_f... for how we do it. 3. Crashes without all the durability settings being on. If you are having to run slave_skip_errors, you are doing it wrong. You should checkout out our automation for backups and restores. They can be found in mysql_restore.py and mysql_backup.py . With regard to PG replication, I suggest you watch https://m.youtube.
Read the rest
com/watch?v=bNeZYVIfskc&t=26m54s Uber had a 16 hours outage in large part caused by pg replication issues. Vacuum issues are also no joke. There are a host of other issues: MySQL can deal with large numbers of connections, PG needs middleware. MySQL is more efficient with "web" workloads where most queries only need to pull on row. etc... -Rob
In Ingesting MySQL data at scale – Part 1

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