[Feature] Using bitmap index to accelerate the query
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- Java
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Description
### Search before asking
- [X] I searched in the [issues](https://github.com/apache/paimon/issues) and found nothing similar.
### Motivation
Currently we have introduced bitmap indexes. There are some optimisations that we can do when the user queries only against the bitmap indexed columns.
Suppose we have a table `usershop_behavior` with a bitmap index on the `gender` column and a bsi index on the `gmv` column.
```sql
CREATE TABLE usershop_behavior (
uid BIGINT
gender STRING,
gmv BIGINT
) WITH (
'file-index.bitmap.columns' = 'gender',
'file-index.bsi.columns' = 'gmv'
);
```
The bitmap index and bsi index can be used not only for filtering, but also for some simple aggregation like:
```sql
SELECT
gender,
COUNT(*) AS total,
SUM(gmv) AS total_gmv,
AVG(gmv) AS avg_gmv
FROM usershop_behavior
GROUP BY gender
SELECT
gender,
COUNT(*) AS total,
SUM(gmv) AS total_gmv,
AVG(gmv) AS avg_gmv
FROM usershop_behavior
WHERE gender='M'
GROUP BY gender
```
BSI index can be useful in topk scenarios
```sql
SELECT *
FROM usershop_behavior
ORDER BY gmv DESC
LIMIT 10;
SELECT *
FROM usershop_behavior
WHERE gender='M'
ORDER BY gmv DESC
LIMIT 10;
```
### Solution
Apache Flink and Apache Spark are already provides some interfaces. e.g.
Apache Flink:
`org.apache.flink.table.connector.source.abilities.SupportsAggregatePushDown`
Apache Spark:
`org.apache.spark.sql.connector.read.SupportsPushDownTopN`
`org.apache.spark.sql.connector.read.SupportsPushDownAggregates`
When queries hit the bitmap index rules, we can rewrite TableScan to BitmapIndexScan.
### Anything else?
Currently our index is designed to be used only for Data Skipping and it is not as reliable as filtering using partitioned keys. (We can't tell the flink&spark engine that filtering with indexes is reliable.)
This is because creating the index is split into several steps.
1. stop the ingesting task
2. using alter table to add index options
3. call rewrite index procedure
4. restart the ingesting task
We need to find a way to make indexes reliable, like partition keys. (e.g. throw exception when index is empty?)
Otherwise it's hard for our index to do its job.
### Are you willing to submit a PR?
- [ ] I'm willing to submit a PR!
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by reviewing the mentioned SupportsAggregatePushDown and SupportsPushDownTopN interfaces, then trace how a TableScan could be rewritten to BitmapIndexScan. Define how bitmap and BSI indexes would support the listed aggregations and top-k queries, including how missing or incomplete indexes should be handled reliably.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- java, spark
- Domain
- data-engineering, databases, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100