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https://issues.apache.org/jira/browse/KYLIN-4829?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17243233#comment-17243233
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ASF GitHub Bot commented on KYLIN-4829:
---------------------------------------
codecov-io commented on pull request #1495:
URL: https://github.com/apache/kylin/pull/1495#issuecomment-738045171
# [Codecov](https://codecov.io/gh/apache/kylin/pull/1495?src=pr&el=h1) Report
> :exclamation: No coverage uploaded for pull request base
(`kylin-on-parquet-v2@d46fc4a`). [Click here to learn what that
means](https://docs.codecov.io/docs/error-reference#section-missing-base-commit).
> The diff coverage is `n/a`.
[](https://codecov.io/gh/apache/kylin/pull/1495?src=pr&el=tree)
```diff
@@ Coverage Diff @@
## kylin-on-parquet-v2 #1495 +/- ##
======================================================
Coverage ? 24.28%
Complexity ? 4616
======================================================
Files ? 1138
Lines ? 64441
Branches ? 9507
======================================================
Hits ? 15651
Misses ? 47156
Partials ? 1634
```
------
[Continue to review full report at
Codecov](https://codecov.io/gh/apache/kylin/pull/1495?src=pr&el=continue).
> **Legend** - [Click here to learn
more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by
[Codecov](https://codecov.io/gh/apache/kylin/pull/1495?src=pr&el=footer). Last
update
[d46fc4a...3b3786c](https://codecov.io/gh/apache/kylin/pull/1495?src=pr&el=lastupdated).
Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
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> Support to use thread-level SparkSession to execute query
> ----------------------------------------------------------
>
> Key: KYLIN-4829
> URL: https://issues.apache.org/jira/browse/KYLIN-4829
> Project: Kylin
> Issue Type: Improvement
> Components: Query Engine, Spark Engine
> Reporter: Zhichao Zhang
> Assignee: Zhichao Zhang
> Priority: Minor
> Fix For: v4.0.0-beta
>
>
> Currently, when executing a query, it is impossible to configure proper
> parameters for each query according to the data will be scanned, such as
> spark.sql.shuffle.partitions, this will impact the performance of querying.
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