Skip to main content

Run large MySQL UPDATE and DELETE queries with small batches to prevent table/row-level locks

Project description

Updating or deleting a large amount of rows in MySQL will create locks that will paralyze other queries running in parallel.

This tool will run UPDATE and DELETE queries in small batches to prevent table-level and row-level locking (with InnoDB). If a large number of rows has to be updated or deleted, it is also possible to limit the number of rows selected at once.

Installation

pip3 install mysql_batch

UPDATE example

You can run this example with the schema available in sample_table/schema.sql

The following example will be identical to the following update:

UPDATE batch_test SET date = NOW() WHERE number > 0.2 AND date is NULL;

This is the equivalent to process this update with batches of 20 rows:

mysql_batch --host localhost \
            --user root \
            --password secret_password \
            --database "test" \
            --table "batch_test" \
            --write_batch_size 20 \
            --where "number > 0.2 AND date IS NULL" \
            --set "date = NOW()"

Output sample:

* Selecting data...
   query: SELECT id as id FROM batch_test WHERE number > 0.2 AND date IS NULL AND id > 0 ORDER BY id LIMIT 1000
* Preparing to modify 83 rows...
* Updating 20 rows...
   query: UPDATE batch_test SET date = NOW() WHERE id IN (1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22)
* Start updating? [Y/n]
* Updating 20 rows...
   query: UPDATE batch_test SET date = NOW() WHERE id IN (23, 25, 26, 28, 29, 30, 31, 33, 35, 36, 37, 38, 39, 40, 42, 43, 44, 45, 46, 47)
* Updating 20 rows...
   query: UPDATE batch_test SET date = NOW() WHERE id IN (48, 49, 50, 51, 52, 53, 54, 55, 56, 58, 59, 60, 61, 63, 64, 65, 68, 69, 70, 71)
* Updating 20 rows...
   query: UPDATE batch_test SET date = NOW() WHERE id IN (72, 74, 75, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 88, 89, 90, 91, 92, 94, 95)
* Updating 3 rows...
   query: UPDATE batch_test SET date = NOW() WHERE id IN (97, 98, 100)
* Selecting data...
   query: SELECT id as id FROM batch_test WHERE number > 0.2 AND date IS NULL AND id > 100 ORDER BY id LIMIT 1000
* No more rows to modify!
* Program exited

DELETE example

The following example will be identical to the following delete:

DELETE FROM batch_test WHERE number > 0.2 AND date is NULL;

This is the equivalent to process this delete with batches of 20 rows:

mysql_batch --host localhost \
            --user root \
            --password secret_password \
            --database "test" \
            --table "batch_test" \
            --write_batch_size 20 \
            --where "number > 0.2 AND date IS NULL" \
            --action "delete"

Output sample:

* Selecting data...
   query: SELECT id as id FROM batch_test WHERE number > 0.2 AND date IS NULL AND id > 0 ORDER BY id LIMIT 1000
* Preparing to modify 79 rows...
* Deleting 20 rows...
   query: DELETE FROM batch_test WHERE id IN (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 17, 19, 20, 21, 22, 23)
* Start deleting? [Y/n]
* Deleting 20 rows...
   query: DELETE FROM batch_test WHERE id IN (24, 25, 26, 28, 34, 35, 36, 37, 38, 39, 40, 41, 44, 45, 47, 48, 50, 51, 52, 53)
* Deleting 20 rows...
   query: DELETE FROM batch_test WHERE id IN (54, 56, 57, 58, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 74, 75, 76)
* Deleting 19 rows...
   query: DELETE FROM batch_test WHERE id IN (77, 78, 79, 80, 82, 83, 86, 87, 88, 89, 90, 91, 93, 94, 95, 96, 98, 99, 100)
* Selecting data...
   query: SELECT id as id FROM batch_test WHERE number > 0.2 AND date IS NULL AND id > 100 ORDER BY id LIMIT 1000
* No more rows to modify!
* Program exited

Usage

usage: mysql_batch [-h] [-H HOST] [-P PORT] -U USER [-p PASSWORD] -d DATABASE
                   -t TABLE [-id PRIMARY_KEY] -w WHERE [-s SET]
                   [-rbz READ_BATCH_SIZE] [-wbz WRITE_BATCH_SIZE] [-S SLEEP]
                   [-a {update,delete}] [-n]

optional arguments:
  -h, --help            show this help message and exit
  -H HOST, --host HOST  MySQL server host
  -P PORT, --port PORT  MySQL server port
  -U USER, --user USER  MySQL user
  -p PASSWORD, --password PASSWORD
                        MySQL password
  -d DATABASE, --database DATABASE
                        MySQL database name
  -t TABLE, --table TABLE
                        MySQL table
  -id PRIMARY_KEY, --primary_key PRIMARY_KEY
                        Name of the primary key column
  -w WHERE, --where WHERE
                        Select WHERE clause
  -s SET, --set SET     Update SET clause
  -rbz READ_BATCH_SIZE, --read_batch_size READ_BATCH_SIZE
                        Select batch size
  -wbz WRITE_BATCH_SIZE, --write_batch_size WRITE_BATCH_SIZE
                        Update/delete batch size
  -S SLEEP, --sleep SLEEP
                        Sleep after each batch
  -a {update,delete}, --action {update,delete}
                        Action ('update' or 'delete')
  -n, --no_confirm      Don't ask for confirmation before to run the write
                        queries

License

This program is under MIT license (view license).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mysql_batch-1.0.4.tar.gz (5.0 kB view details)

Uploaded Source

Built Distribution

mysql_batch-1.0.4-py2.py3-none-any.whl (8.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file mysql_batch-1.0.4.tar.gz.

File metadata

  • Download URL: mysql_batch-1.0.4.tar.gz
  • Upload date:
  • Size: 5.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for mysql_batch-1.0.4.tar.gz
Algorithm Hash digest
SHA256 681a8013d28e722df5d7d0f30861298bb3408efa3562a77c5a99d7d403b04514
MD5 eb1d247cc0b03964f509bfeec1324f77
BLAKE2b-256 ed4741cab317088fdbd4186f744ef7957985b1e0ff36c296b26c99c0cc361053

See more details on using hashes here.

File details

Details for the file mysql_batch-1.0.4-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for mysql_batch-1.0.4-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 2e36b13485edf1371ecd756837b30263c3a384312540a8eec547bc58d64d1924
MD5 bd02ff6e2636986508a6b1191d02a90d
BLAKE2b-256 e76c93c3d43f1f6194940035405f491d752a6fd268c971f8ff80cca2e4198d30

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page