Hi All,
I want to improve hudi‘s index. There are four main steps to achieve this
1. Implement index syntax
a. Implement index syntax for spark sql [1] , I have submitted the
first pr.
b. Implement index syntax for prestodb sql
c. Implement index syntax for trino sql
2. read/write index decoupling
The read/write index is decoupled from the computing engine side, and the
sql index syntax of the first step can be independently executed and called
through the API.
3. build index service
Promote the implementation of the hudi service framework, including index
service, metastore service[2], compact/cluster service[3], etc.
4. Index Management
There are two kinds of management semantic for Index.
- Automatic Refresh
- Manual Refresh
1. Automatic Refresh
When a user creates an index on the main table without using WITH DEFERRED
REFRESH syntax, the index will be managed by the system automatically. For
every data load to the main table, the system will immediately trigger a
load to the index automatically. These two data loading (to main table and
index) is executed in a transactional manner, meaning that it will be
either both success or neither success.
The data loading to index is incremental based on Segment concept, avoiding
an expensive total refresh.
If a user performs the following command on the main table, the system will
return failure. (reject the operation)
- Data management command: UPDATE/DELETE/DELETE SEGMENT.
- Schema management command: ALTER TABLE DROP COLUMN, ALTER TABLE CHANGE
DATATYPE, ALTER TABLE RENAME. Note that adding a new column is supported,
and for dropping columns and change datatype command, CarbonData will check
whether it will impact the index table, if not, the operation is allowed,
otherwise operation will be rejected by throwing an exception.
- Partition management command: ALTER TABLE ADD/DROP PARTITION.
If a user does want to perform above operations on the main table, the user
can first drop the index, perform the operation, and re-create the index
again.
If a user drops the main table, the index will be dropped immediately too.
We do recommend you to use this management for indexing.
2. Manual Refresh
When a user creates an index on the main table using WITH DEFERRED REFRESH
syntax, the index will be created with status disabled and query will NOT
use this index until the user issues REFRESH INDEX command to build the
index. For every REFRESH INDEX command, the system will trigger a full
refresh of the index. Once the refresh operation is finished, system will
change index status to enabled, so that it can be used in query rewrite.
For every new data loading, data update, delete, the related index will be
made disabled, which means that the following queries will not benefit from
the index before it becomes enabled again.
If the main table is dropped by the user, the related index will be dropped
immediately.
Any feedback is welcome!
Thank you.
Regards,
Forward Xu
Related Links:
[1] Implement index syntax for spark sql
<https://issues.apache.org/jira/browse/HUDI-3881>
[2] Metastore service <https://github.com/apache/hudi/pull/5064>
[3] <https://github.com/apache/hudi/pull/4872>compaction/clustering job in
Service <https://github.com/apache/hudi/pull/4872>
