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Posted to issues@paimon.apache.org by "JingsongLi (via GitHub)" <gi...@apache.org> on 2023/03/29 01:51:08 UTC
[GitHub] [incubator-paimon] JingsongLi opened a new issue, #735: [Feature] Support materialized column to improve query performance for complex types
JingsongLi opened a new issue, #735:
URL: https://github.com/apache/incubator-paimon/issues/735
### Search before asking
- [X] I searched in the [issues](https://github.com/apache/incubator-paimon/issues) and found nothing similar.
### Motivation
In the world of data warehouse, it is very common to use one or more columns from a complex type such as a map, or to put many subfields into it. These operations can greatly affect query performance because:
1. These operations are very wasteful IO. For example, if we have a field type of Map, which contains dozens of subfields, we need to read the entire column when reading this column. And Spark will traverse the entire map to get the value of the target key.
2. Cannot take advantage of vectorized reads when reading nested type columns.
3. Filter pushdown cannot be used when reading nested columns.
It is necessary to introduce the materialized column feature in Flink Table Store, which transparently solves the above problems of arbitrary columnar storage (not just Parquet).
### Solution
_No response_
### Anything else?
_No response_
### Are you willing to submit a PR?
- [ ] I'm willing to submit a PR!
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[GitHub] [incubator-paimon] zhangjun0x01 commented on issue #735: [Feature] Support materialized column to improve query performance for complex types
Posted by "zhangjun0x01 (via GitHub)" <gi...@apache.org>.
zhangjun0x01 commented on issue #735:
URL: https://github.com/apache/incubator-paimon/issues/735#issuecomment-1492181024
clickhouse support the feature by `ALTER TABLE`, like `ALTER TABLE events
ADD COLUMN mat_$current_url
VARCHAR MATERIALIZED JSONExtractString(properties_json, '$current_url')` ,but flink and spark do not support the statement, do we implement it by add some properties?
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