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Posted to commits@pinot.apache.org by GitBox <gi...@apache.org> on 2021/11/30 13:39:31 UTC
[GitHub] [pinot] Eywek opened a new issue #7842: feature request: `LIKE` operator in `JSON_MATCH`
Eywek opened a new issue #7842:
URL: https://github.com/apache/pinot/issues/7842
Hello,
I was wondering if it was planned to add the LIKE operator to JSON_MATCH ? I’m currently using
```sql
REGEXP_LIKE(JSONEXTRACTSCALAR("labels", '$.demande_intention', 'STRING'), 'terminal')
```
but it’s very slow (even with small number of scanned documents (21). And I was thinking that maybe having it directly with JSON_MATCH could speed-up this operation?
```sql
JSON_MATCH("labels", 'demande_intention LIKE ''terminal''')
```
Thank you
cc @atris
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[GitHub] [pinot] richardstartin commented on issue #7842: feature request: `LIKE` operator in `JSON_MATCH`
Posted by GitBox <gi...@apache.org>.
richardstartin commented on issue #7842:
URL: https://github.com/apache/pinot/issues/7842#issuecomment-982651511
Hi @Eywek how slow is "very slow"?
Is there a natural way for you to filter the JSON documents before applying the `JSONEXTRACTSCALAR` and `REGEXP_LIKE` functions? Without an index structured to support these functions, they are naturally quite expensive.
Have you considered extracting `$.demande_intention` into a text column during ingestion so you can create a text index on it, instead of storing it embedded in JSON?
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[GitHub] [pinot] Eywek commented on issue #7842: feature request: `LIKE` operator in `JSON_MATCH`
Posted by GitBox <gi...@apache.org>.
Eywek commented on issue #7842:
URL: https://github.com/apache/pinot/issues/7842#issuecomment-982655500
> how slow is "very slow"?
~600-800ms for 21 documents (vs 22-40ms without this filter)
> Is there a natural way for you to filter the JSON documents before applying the `JSONEXTRACTSCALAR` and `REGEXP_LIKE` functions? Without an index structured to support these functions, they are naturally quite expensive.
I'm using a JSON index on the column and operations like `JSON_MATCH(labels, 'demande_intention = ''foo''')` are fast (30-40ms)
> Have you considered extracting `$.demande_intention` into a text column during ingestion so you can create a text index on it, instead of storing it embedded in JSON?
Yep I know it would be the best way to do it but since the `labels` column contains dynamic data, we don't want to add each field of the JSON object to the schema
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