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Posted to reviews@spark.apache.org by "Hisoka-X (via GitHub)" <gi...@apache.org> on 2023/10/06 05:15:00 UTC
[PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Hisoka-X opened a new pull request, #43243:
URL: https://github.com/apache/spark/pull/43243
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### What changes were proposed in this pull request?
This PR fix CSV/JSON schema inference when timestamps do not match specified timestampFormat will report error.
```scala
//eg
val csv = spark.read.option("timestampFormat", "yyyy-MM-dd'T'HH:mm:ss")
.option("inferSchema", true).csv(Seq("2884-06-24T02:45:51.138").toDS())
csv.show()
//error
Caused by: java.time.format.DateTimeParseException: Text '2884-06-24T02:45:51.138' could not be parsed, unparsed text found at index 19
```
This bug only happend when partition had one row. The data type should be `StringType` not `TimestampType` because the value not match `timestampFormat`.
Use csv as eg, in `CSVInferSchema::tryParseTimestampNTZ`, first, use `timestampNTZFormatter.parseWithoutTimeZoneOptional` to inferring return `TimestampType`, if same partition had another row, it will use `tryParseTimestamp` to parse row with user defined `timestampFormat`, then found it can't be convert to timestamp with `timestampFormat`. Finally return `StringType`. But when only one row, we use `timestampNTZFormatter.parseWithoutTimeZoneOptional` to parse normally timestamp not right. We should only parse it when `spark.sql.timestampType` is `TIMESTAMP_NTZ`. If `spark.sql.timestampType` is `TIMESTAMP_LTZ`, we should directly parse it use `tryParseTimestamp`. To avoid return `TimestampType` when timestamps do not match specified timestampFormat.
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### Why are the changes needed?
Fix schema inference bug.
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### Does this PR introduce _any_ user-facing change?
No
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### How was this patch tested?
add new test.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on PR #43243:
URL: https://github.com/apache/spark/pull/43243#issuecomment-1752867584
> This PR base on https://github.com/apache/spark/pull/43245
The dependency has been merged. Could you rebase this PR, please.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454903572
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
Yep, but it only happened when use legacy mode. Feel free to change it if you think the legacy behavior not right.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454478275
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
I did some test use old version which before this PR merged. When `SQLConf.get.timestampType == TIMESTAMP_LTZ`, it used `timestampNTZFormatter` to parsed timestamp and passed. You can use `CSVLegacyTimeParserSuite.SPARK-37326: Timestamp type inference for a column with TIMESTAMP_NTZ values` to reproduce this behavior.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454500823
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
The purpose of adding `legacyTimeParserPolicy == LEGACY` is to keep the legacy behavior unchanged. But legacy’s behavior is indeed not correct.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk closed pull request #43243: [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat
URL: https://github.com/apache/spark/pull/43243
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454667685
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
Because the string format are same of two type.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454801365
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
Then we hit the else branch and `tryParseTimestamp` can infer the type properly?
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454811586
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
According test case, I think yes. Is any case not right now?
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454861501
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
The code looks wrong, we may infer ltz using the nzt formatter. This can be a potential bug and bite us in the future.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on PR #43243:
URL: https://github.com/apache/spark/pull/43243#issuecomment-1750008068
cc @MaxGekk @gengliangwang
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on PR #43243:
URL: https://github.com/apache/spark/pull/43243#issuecomment-1750184945
This PR base on #43245
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1351132582
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
1. Because the `LEGACY` behavior used `timestampNTZFormatter` to parse timestamp. So I don't change it when use `LEGACY` mode. Without this, some test case like `CSVLegacyTimeParserSuite.SPARK-37326: Timestamp type inference for a column with TIMESTAMP_NTZ values` can't passed. https://github.com/Hisoka-X/spark/runs/17462554632
2. It should be `(legacyTimeParserPolicy = LEGACY || timestampType == TimestampNTZType)` not `(legacyTimeParserPolicy = LEGACY || timestampType == TimestampLTZType)` if I think correctly.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on PR #43243:
URL: https://github.com/apache/spark/pull/43243#issuecomment-1758078451
@Hisoka-X Could you backport this changes to `branch-3.4`. This PR fails on 3.4:
```
[error] /Users/maximgekk/proj/review-Hisoka-X_SPARK-45433-inference-mismatch-timestamp-one-row-3.4/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:30:8: object LegacyBehaviorPolicy is not a member of package org.apache.spark.sql.internal
[error] import org.apache.spark.sql.internal.{LegacyBehaviorPolicy, SQLConf}
[error] ^
[error] /Users/maximgekk/proj/review-Hisoka-X_SPARK-45433-inference-mismatch-timestamp-one-row-3.4/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:206:48: not found: value LegacyBehaviorPolicy
[error] if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
[error]
```
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on PR #43243:
URL: https://github.com/apache/spark/pull/43243#issuecomment-1758058111
+1, LGTM. Merging to master/3.5.
Thank you, @Hisoka-X.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454495232
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
so the condition here should just be `timestampType == TimestampNTZType`?
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on PR #43243:
URL: https://github.com/apache/spark/pull/43243#issuecomment-1752954502
> > This PR base on #43245
>
> The dependency has been merged. Could you rebase this PR, please.
Done. Thanks @MaxGekk
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1350458288
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
also cc @gengliangwang
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1355316434
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
> Because the LEGACY behavior used timestampNTZFormatter to parse timestamp.
I see. It is ok if the such legacy behaviour is covered by a test.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1350457873
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
Could you clarify this:
(legacyTimeParserPolicy = LEGACY || timestampType == TimestampLTZType)
we are trying to parse it as NTZ, and it is parsable we return `TimestampLTZType`?
This confuses me, return `TIMESTAMP LTZ` when the input was parsed by a NTZ function.
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454349106
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
> Because the LEGACY behavior used timestampNTZFormatter to parse timestamp.
I can't find the related code, @Hisoka-X can you point to it?
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Re: [PR] [SPARK-45433][SQL] Fix CSV/JSON schema inference when timestamps do not match specified timestampFormat [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #43243:
URL: https://github.com/apache/spark/pull/43243#discussion_r1454503456
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
##########
@@ -202,8 +202,11 @@ 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.
- if (timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
- SQLConf.get.timestampType
+ val timestampType = SQLConf.get.timestampType
+ if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
+ timestampType == TimestampNTZType) &&
+ timestampNTZFormatter.parseWithoutTimeZoneOptional(field, false).isDefined) {
Review Comment:
My point is we should fully understand the code before making changes. Why do we ever use ntz formatter to infer ltz type?
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