[SPARK-40215][SQL] Add SQL configs to control CSV/JSON date and timestamp parsing behavior #37653
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
sadikovi
changed the title
Contributor
Author
|
@HyukjinKwon @MaxGekk Could you review this PR? Thank you. |
HyukjinKwon
approved these changes
Aug 25, 2022
MaxGekk
reviewed
Aug 25, 2022
Member
MaxGekk
left a comment
MaxGekk
left a comment
There was a problem hiding this comment.
I wonder what is supposed life time of the SQL configs spark.sql.*.enableDateTimeParsingFallback? Should we place them in the spark.sql.legacy namespace similar to spark.sql.legacy.timeParserPolicy.
Contributor
Author
|
I just wanted to keep the option name short have a custom build already with those configs but I can move them under legacy, e.g. |
sadikovi
commented
Aug 26, 2022
|
|
||
| def avroFilterPushDown: Boolean = getConf(AVRO_FILTER_PUSHDOWN_ENABLED) | ||
|
|
||
| def jsonEnableDateTimeParsingFallback: Option[Boolean] = |
Contributor
Author
There was a problem hiding this comment.
I decided not to add "legacy" prefix in the method as it would make the method name very long 🙂.
Contributor
Author
|
@MaxGekk I addressed your comment. Would you be able to review again? Thanks. |
MaxGekk
approved these changes
Aug 26, 2022
Member
|
+1, LGTM. Merging to master. |
Contributor
Author
|
Thank you, @MaxGekk! |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
4 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
What changes were proposed in this pull request?
This is a follow-up for SPARK-39731 and PR #37147.
I found that it could be problematic to change
spark.sql.legacy.timeParserPolicyto LEGACY when inferring dates and timestamps in CSV and JSON. Sometimes it is beneficial to have the time parser policy as CORRECTED but still use a more lenient date and timestamp inference (or when migrating to a newer Spark version).I added two separate configs that control this behavior:
spark.sql.legacy.csv.enableDateTimeParsingFallbackspark.sql.legacy.json.enableDateTimeParsingFallbackWhen the configs are set to
true, the legacy time parsing behaviour is enabled (pre Spark 3.0).With this PR, the precedence order is as follows for CSV (similar for JSON):
enableDateTimeParsingFallbackspark.sql.legacy.{csv,json}.enableDateTimeParsingFallbackspark.sql.legacy.timeParserPolicyand whether or not a custom format is used.Why are the changes needed?
The change makes it easier for users to migrate to a newer Spark version without changing global config
spark.sql.legacy.timeParserPolicy. Also, allows to enable legacy parsing for CSV and JSON separately without changing the code or the global time parser config.Does this PR introduce any user-facing change?
No, simply adds an ability to change the behaviour specifically for CSV or JSON.
How was this patch tested?
I added a unit test for CSV and JSON to verify the flag.