Int range partitioning
- Introduced in GitLab 16.8.
Description
Int range partitioning is a technique for dividing a large table into smaller, more manageable chunks based on an integer column. This can be particularly useful for tables with large numbers of rows, as it can significantly improve query performance, reduce storage requirements, and simplify maintenance tasks. For this type of partitioning to work well, most queries must access data in a certain int range.
To look at this in more detail, imagine a simplified merge_request_diff_files
schema:
CREATE TABLE merge_request_diff_files (
merge_request_diff_id INT NOT NULL,
relative_order INT NOT NULL,
PRIMARY KEY (merge_request_diff_id, relative_order));
Now imagine typical queries in the UI would display the data in a certain int range:
SELECT *
FROM merge_request_diff_files
WHERE merge_request_diff_id > 1 AND merge_request_diff_id < 10
LIMIT 100
If the table is partitioned on the merge_request_diff_id
column the base table would look like:
CREATE TABLE merge_request_diff_files (
merge_request_diff_id INT NOT NULL,
relative_order INT NOT NULL,
PRIMARY KEY (merge_request_diff_id, relative_order))
PARTITION BY RANGE(merge_request_diff_id);
And we might have a list of partitions for the table, such as:
merge_request_diff_files_1 FOR VALUES FROM (1) TO (20)
merge_request_diff_files_20 FOR VALUES FROM (20) TO (40)
merge_request_diff_files_40 FOR VALUES FROM (40) TO (60)
Each partition is a separate physical table, with the same structure as
the base merge_request_diff_files
table, but contains only data for rows where the
partition key falls in the specified range. For example, the partition
merge_request_diff_files_1
contains rows where the merge_request_diff_id
column is
greater than or equal to 1
and less than 20
.
Now, if we look at the previous example query again, the database can
use the WHERE
to recognize that all matching rows are in the
merge_request_diff_files_1
partition. Rather than searching all of the data
in all of the partitions. In a large table, this can
dramatically reduce the amount of data the database needs to access.
Example
Step 1: Creating the partitioned copy (Release N)
The first step is to add a migration to create the partitioned copy of the original table. This migration creates the appropriate partitions based on the data in the original table, and install a trigger that syncs writes from the original table into the partitioned copy.
An example migration of partitioning the merge_request_diff_commits
table by its
merge_request_diff_id
column would look like:
class PartitionMergeRequestDiffCommits < Gitlab::Database::Migration[2.1]
include Gitlab::Database::PartitioningMigrationHelpers
disable_ddl_transaction!
def up
partition_table_by_int_range(
'merge_request_diff_commits',
'merge_request_diff_id',
partition_size: 10_000_000,
primary_key: %w[merge_request_diff_id relative_order]
)
end
def down
drop_partitioned_table_for('merge_request_diff_commits')
end
end
After this has executed, any inserts, updates, or deletes in the original table are also duplicated in the new table. For updates and deletes, the operation only has an effect if the corresponding row exists in the partitioned table.
Step 2: Backfill the partitioned copy (Release N)
The second step is to add a post-deployment migration that schedules the background jobs that backfill existing data from the original table into the partitioned copy.
Continuing the above example, the migration would look like:
class BackfillPartitionMergeRequestDiffCommits < Gitlab::Database::Migration[2.2]
include Gitlab::Database::PartitioningMigrationHelpers
milestone '16.10'
disable_ddl_transaction!
restrict_gitlab_migration gitlab_schema: :gitlab_main
def up
enqueue_partitioning_data_migration :merge_request_diff_commits
end
def down
cleanup_partitioning_data_migration :merge_request_diff_commits
end
end
This step queues a batched background migration internally with BATCH_SIZE and SUB_BATCH_SIZE as 50,000
and 2,500
. Refer Batched Background migrations guide for more details.
Step 3: Post-backfill cleanup (Release N+1)
This step must occur at least one release after the release that includes step (2). This gives time for the background migration to execute properly in self-managed installations. In this step, add another post-deployment migration that cleans up after the background migration. This includes forcing any remaining jobs to execute, and copying data that may have been missed, due to dropped or failed jobs.
Once again, continuing the example, this migration would look like:
class CleanupPartitionMergeRequestDiffCommitsBackfill < Gitlab::Database::Migration[2.1]
include Gitlab::Database::PartitioningMigrationHelpers
disable_ddl_transaction!
restrict_gitlab_migration gitlab_schema: :gitlab_main
def up
finalize_backfilling_partitioned_table :merge_request_diff_commits
end
def down
# no op
end
end
After this migration completes, the original table and partitioned table should contain identical data. The trigger installed on the original table guarantees that the data remains in sync going forward.
Step 4: Swap the partitioned and non-partitioned tables (Release N+1)
This step replaces the non-partitioned table with its partitioned copy, this should be used only after all other migration steps have completed successfully.
Some limitations to this method MUST be handled before, or during, the swap migration:
- Secondary indexes and foreign keys are not automatically recreated on the partitioned table.
- Some types of constraints (UNIQUE and EXCLUDE) which rely on indexes, are not automatically recreated on the partitioned table, since the underlying index will not be present.
- Foreign keys referencing the original non-partitioned table should be updated to reference the partitioned table. This is not supported in PostgreSQL 11.
- Views referencing the original table are not automatically updated to reference the partitioned table.
# frozen_string_literal: true
class SwapPartitionMergeRequestDiffCommits < ActiveRecord::Migration[6.0]
include Gitlab::Database::PartitioningMigrationHelpers
def up
replace_with_partitioned_table :audit_events
end
def down
rollback_replace_with_partitioned_table :audit_events
end
end
After this migration completes:
- The partitioned table replaces the non-partitioned (original) table.
- The sync trigger created earlier is dropped.
The partitioned table is now ready for use by the application.