You are viewing a plain text version of this content. The canonical link for it is here.
Posted to reviews@spark.apache.org by "MaxGekk (via GitHub)" <gi...@apache.org> on 2024/01/18 16:33:38 UTC
[PR] [WIP][SQL] Don't use the NTZ parser for inferring TIMESTAMP_LTZ in CSV [spark]
MaxGekk opened a new pull request, #44789:
URL: https://github.com/apache/spark/pull/44789
<!--
Thanks for sending a pull request! Here are some tips for you:
1. If this is your first time, please read our contributor guidelines: https://spark.apache.org/contributing.html
2. Ensure you have added or run the appropriate tests for your PR: https://spark.apache.org/developer-tools.html
3. If the PR is unfinished, add '[WIP]' in your PR title, e.g., '[WIP][SPARK-XXXX] Your PR title ...'.
4. Be sure to keep the PR description updated to reflect all changes.
5. Please write your PR title to summarize what this PR proposes.
6. If possible, provide a concise example to reproduce the issue for a faster review.
7. If you want to add a new configuration, please read the guideline first for naming configurations in
'core/src/main/scala/org/apache/spark/internal/config/ConfigEntry.scala'.
8. If you want to add or modify an error type or message, please read the guideline first in
'core/src/main/resources/error/README.md'.
-->
### What changes were proposed in this pull request?
<!--
Please clarify what changes you are proposing. The purpose of this section is to outline the changes and how this PR fixes the issue.
If possible, please consider writing useful notes for better and faster reviews in your PR. See the examples below.
1. If you refactor some codes with changing classes, showing the class hierarchy will help reviewers.
2. If you fix some SQL features, you can provide some references of other DBMSes.
3. If there is design documentation, please add the link.
4. If there is a discussion in the mailing list, please add the link.
-->
### Why are the changes needed?
<!--
Please clarify why the changes are needed. For instance,
1. If you propose a new API, clarify the use case for a new API.
2. If you fix a bug, you can clarify why it is a bug.
-->
### Does this PR introduce _any_ user-facing change?
<!--
Note that it means *any* user-facing change including all aspects such as the documentation fix.
If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible.
If possible, please also clarify if this is a user-facing change compared to the released Spark versions or within the unreleased branches such as master.
If no, write 'No'.
-->
### How was this patch tested?
<!--
If tests were added, say they were added here. Please make sure to add some test cases that check the changes thoroughly including negative and positive cases if possible.
If it was tested in a way different from regular unit tests, please clarify how you tested step by step, ideally copy and paste-able, so that other reviewers can test and check, and descendants can verify in the future.
If tests were not added, please describe why they were not added and/or why it was difficult to add.
If benchmark tests were added, please run the benchmarks in GitHub Actions for the consistent environment, and the instructions could accord to: https://spark.apache.org/developer-tools.html#github-workflow-benchmarks.
-->
### Was this patch authored or co-authored using generative AI tooling?
<!--
If generative AI tooling has been used in the process of authoring this patch, please include the
phrase: 'Generated-by: ' followed by the name of the tool and its version.
If no, write 'No'.
Please refer to the [ASF Generative Tooling Guidance](https://www.apache.org/legal/generative-tooling.html) for details.
-->
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org
Re: [PR] [SPARK-46769][SQL] Fix type inferring for timestamps without time zone in JSON/CSV [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #44789:
URL: https://github.com/apache/spark/pull/44789#discussion_r1458649995
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,11 +202,8 @@ class CSVInferSchema(val options: CSVOptions) extends Serializable {
// We can only parse the value as TimestampNTZType if it does not have zone-offset or
// time-zone component and can be parsed with the timestamp formatter.
// Otherwise, it is likely to be a timestamp with timezone.
- val timestampType = SQLConf.get.timestampType
- if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
- timestampType == TimestampNTZType) &&
- timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- timestampType
+ if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
+ SQLConf.get.timestampType
Review Comment:
I think it's literally wrong to infer a value as LTZ type by using the NTZ parser.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org
Re: [PR] [SPARK-46769][SQL] Fix type inferring for timestamps without time zone in JSON/CSV [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #44789:
URL: https://github.com/apache/spark/pull/44789#discussion_r1458636982
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,11 +202,8 @@ class CSVInferSchema(val options: CSVOptions) extends Serializable {
// We can only parse the value as TimestampNTZType if it does not have zone-offset or
// time-zone component and can be parsed with the timestamp formatter.
// Otherwise, it is likely to be a timestamp with timezone.
- val timestampType = SQLConf.get.timestampType
- if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
- timestampType == TimestampNTZType) &&
- timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- timestampType
+ if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
+ SQLConf.get.timestampType
Review Comment:
Does this assume the LTZ parser can parse NTZ values? But it isn't true if LTZ and NTZ have different parsing patterns?
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,11 +202,8 @@ class CSVInferSchema(val options: CSVOptions) extends Serializable {
// We can only parse the value as TimestampNTZType if it does not have zone-offset or
// time-zone component and can be parsed with the timestamp formatter.
// Otherwise, it is likely to be a timestamp with timezone.
- val timestampType = SQLConf.get.timestampType
- if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
- timestampType == TimestampNTZType) &&
- timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- timestampType
+ if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
+ SQLConf.get.timestampType
Review Comment:
Does this assume the LTZ parser can parse NTZ values? But it isn't true if LTZ and NTZ have different parsing patterns.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org
Re: [PR] [SPARK-46769][SQL] Fix inferring TIMESTAMP_NTZ in JSON/CSV [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on PR #44789:
URL: https://github.com/apache/spark/pull/44789#issuecomment-1899827649
also cc @Hisoka-X @sadikovi
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org
Re: [PR] [SPARK-46769][SQL] Fix type inferring for timestamps without time zone in JSON/CSV [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan closed pull request #44789: [SPARK-46769][SQL] Fix type inferring for timestamps without time zone in JSON/CSV
URL: https://github.com/apache/spark/pull/44789
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org
Re: [PR] [SPARK-46769][SQL] Fix inferring TIMESTAMP_NTZ in JSON/CSV [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on code in PR #44789:
URL: https://github.com/apache/spark/pull/44789#discussion_r1458402959
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,11 +202,8 @@ class CSVInferSchema(val options: CSVOptions) extends Serializable {
// We can only parse the value as TimestampNTZType if it does not have zone-offset or
// time-zone component and can be parsed with the timestamp formatter.
// Otherwise, it is likely to be a timestamp with timezone.
- val timestampType = SQLConf.get.timestampType
- if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
- timestampType == TimestampNTZType) &&
- timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- timestampType
+ if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
+ SQLConf.get.timestampType
Review Comment:
Restored to the state of https://github.com/apache/spark/pull/40022
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org
Re: [PR] [SPARK-46769][SQL] Fix inferring TIMESTAMP_NTZ in JSON/CSV [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on code in PR #44789:
URL: https://github.com/apache/spark/pull/44789#discussion_r1458404759
##########
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchemaSuite.scala:
##########
@@ -267,7 +267,9 @@ class CSVInferSchemaSuite extends SparkFunSuite with SQLHelper {
test("SPARK-45433: inferring the schema when timestamps do not match specified timestampFormat" +
" with only one row") {
val options = new CSVOptions(
- Map("timestampFormat" -> "yyyy-MM-dd'T'HH:mm:ss"),
+ Map(
+ "timestampFormat" -> "yyyy-MM-dd'T'HH:mm:ss",
+ "timestampNTZFormat" -> "yyyy-MM-dd HH:mm:ss"),
Review Comment:
To infer the STRING type, the input must not match to **both** formats: `TIMESTAMP` and `TIMESTAMP_NTZ`. Just set `timestampFormat` is not enough.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org
Re: [PR] [SPARK-46769][SQL] Fix type inferring for timestamps without time zone in JSON/CSV [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #44789:
URL: https://github.com/apache/spark/pull/44789#discussion_r1458648993
##########
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchemaSuite.scala:
##########
@@ -267,7 +267,9 @@ class CSVInferSchemaSuite extends SparkFunSuite with SQLHelper {
test("SPARK-45433: inferring the schema when timestamps do not match specified timestampFormat" +
" with only one row") {
val options = new CSVOptions(
- Map("timestampFormat" -> "yyyy-MM-dd'T'HH:mm:ss"),
+ Map(
+ "timestampFormat" -> "yyyy-MM-dd'T'HH:mm:ss",
+ "timestampNTZFormat" -> "yyyy-MM-dd HH:mm:ss"),
Review Comment:
I don't agree. A query fails if an option is not set is not really a good behavior.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org