GitHub user avamingli edited a discussion: Supporting Partitioned Tables in
AQUMV(Answer Query Using Materialized Views)
### Description
Partitioned tables are essential for optimizing query performance in OLAP
environments.
They allow for more efficient data management and retrieval by dividing large
datasets into smaller, more manageable pieces.
Cloudberry currently offers the AQUMV (Answer Query Using Materialized Views)
feature, which significantly improves query performance. However, at present,
it only supports queries on a single base table or a foreign table.
Given the widespread use of partitioned tables in OLAP databases, I propose
that we extend AQUMV to support partitioned tables.
This enhancement involves two main components:
1. Data Status Maintenance for Partitioned Tables:
When writable operations such as INSERT, UPDATE, DELETE, or TRUNCATE occur on
a base table, the data status of the
associated materialized view changes.
For partitioned tables, this process is more complex. Since a partitioned
table
typically has a partition tree, changes to a child partition can affect its
parent table and potentially all ancestor tables.
Consequently, materialized views that reference these tables may also need to
update their data status.
For example, consider a root partitioned table P0 with two child
partitioned tables: P1 and P2. Each child table further has
two sub-partitions: P1 has P1_1 and P1_2, while P2 has P2_1 and P2_2.
If we insert rows into P1_1, the data status of both mv0 (based on P0) and
mv1 (based on P1) will change, as P1_1's parent table P1 and the root table P0
now contain more rows.
Conversely, if we insert rows into P2_1, only the data status of mv2_1
(based on P2_1) and mv0 will be affected, while mv1 remains unchanged because
the data in P1 has not changed.
![Uploading q_dynamic_table.drawio3.svg…]()
3. SQL Query Rewriting in the Planner:
The AQUMV should also be able to rewrite SQL queries to utilize materialized
views instead of querying partitioned tables directly. This would enable users
to take full advantage of the performance benefits offered by materialized
views while working with partitioned data.
By supporting partitioned tables within the AQUMV feature, we can significantly
enhance the usability and performance of Cloudberry in OLAP scenarios. This
enhancement will not only improve query performance , catering to the growing
needs of users who rely on partitioned tables for efficient data management and
analysis.
### Use case/motivation
_No response_
### Related issues
_No response_
### Are you willing to submit a PR?
- [X] Yes I am willing to submit a PR!
GitHub link: https://github.com/apache/cloudberry/discussions/780
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