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[SPARK-14922][SPARK-17732][SPARK-23866][SQL] Support partition filters in ALTER TABLE DROP PARTITION #20999
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Test build #88996 has finished for PR 20999 at commit
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thanks @gatorsmile , I missed them. I see that #19691 is still open and waiting for review. Probably I should close this one and we can go on on that PR. But I have seen no activity on it for a while, is there any reason? Thanks. |
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| dropPartitionVal | ||
| : identifier (comparisonOperator constant)? |
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It has to be in this format? partCol1 > 2 How about 2 > partCol1?
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yes, in Hive it has to be like this. 2 > partCol1 is not supported by Hive.
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Hive also throws antler errors for the case 2 > partCol1?
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Hive does throw an error in that case, you mean asking that error is a parsing or another kind of exception?
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yea, yes. I like user-understandable error messages.
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Hive throws this parser exception:
hive> alter table test1 drop partition(1 > c);
NoViableAltException(368@[])
at org.apache.hadoop.hive.ql.parse.HiveParser_IdentifiersParser.identifier(HiveParser_IdentifiersParser.java:12014)
at org.apache.hadoop.hive.ql.parse.HiveParser_IdentifiersParser.dropPartitionVal(HiveParser_IdentifiersParser.java:11684)
at org.apache.hadoop.hive.ql.parse.HiveParser_IdentifiersParser.dropPartitionSpec(HiveParser_IdentifiersParser.java:11563)
at org.apache.hadoop.hive.ql.parse.HiveParser.dropPartitionSpec(HiveParser.java:44851)
at org.apache.hadoop.hive.ql.parse.HiveParser.alterStatementSuffixDropPartitions(HiveParser.java:11564)
at org.apache.hadoop.hive.ql.parse.HiveParser.alterTableStatementSuffix(HiveParser.java:8000)
at org.apache.hadoop.hive.ql.parse.HiveParser.alterStatement(HiveParser.java:7450)
at org.apache.hadoop.hive.ql.parse.HiveParser.ddlStatement(HiveParser.java:4340)
at org.apache.hadoop.hive.ql.parse.HiveParser.execStatement(HiveParser.java:2497)
at org.apache.hadoop.hive.ql.parse.HiveParser.statement(HiveParser.java:1423)
at org.apache.hadoop.hive.ql.parse.ParseDriver.parse(ParseDriver.java:209)
at org.apache.hadoop.hive.ql.parse.ParseUtils.parse(ParseUtils.java:74)
at org.apache.hadoop.hive.ql.parse.ParseUtils.parse(ParseUtils.java:67)
at org.apache.hadoop.hive.ql.Driver.compile(Driver.java:615)
at org.apache.hadoop.hive.ql.Driver.compileInternal(Driver.java:1829)
at org.apache.hadoop.hive.ql.Driver.compileAndRespond(Driver.java:1776)
at org.apache.hadoop.hive.ql.Driver.compileAndRespond(Driver.java:1771)
at org.apache.hadoop.hive.ql.reexec.ReExecDriver.compileAndRespond(ReExecDriver.java:126)
at org.apache.hadoop.hive.ql.reexec.ReExecDriver.run(ReExecDriver.java:214)
at org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:239)
at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:188)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:402)
at org.apache.hadoop.hive.cli.CliDriver.executeDriver(CliDriver.java:832)
at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:770)
at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:694)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:221)
at org.apache.hadoop.util.RunJar.main(RunJar.java:136)
FAILED: ParseException line 1:33 cannot recognize input near '1' '>' 'c' in drop partition statement
so yes, it is analogous to this.
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thanks for the check. I still like meaningful messages though, we shold wait for other reviewer's comments.
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Let us start reviewing that PR. |
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ok, thanks @gatorsmile. Then I am closing this. |
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I am reopening this according to the discussion in #19691. |
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Test build #95725 has finished for PR 20999 at commit
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still WIP? btw, it seems currently credits can go to multiple developers; |
Yes, but I don't know how to do that. Probably committers can do it in the merging process, so I think the only thing I can do is write in the description who should be credited and then committers can do accordingly. Please correct me if I am wrong. Thanks. |
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Test build #95758 has finished for PR 20999 at commit
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you're not wrong, but I just meant you don't need to describe "Credit for that should be given to him." in the PR description. |
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Thanks @maropu , updated. |
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| dropPartitionVal | ||
| : identifier (comparisonOperator constant)? |
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Hive also throws antler errors for the case 2 > partCol1?
| test("SPARK-14922: Partition filter is not allowed in ADD PARTITION") { | ||
| withTable("sales") { | ||
| sql("CREATE TABLE sales(id INT) PARTITIONED BY (country STRING, quarter STRING)") | ||
| intercept[AnalysisException] { |
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plz check all the error messages above?
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ok, will do
| val tableIdent = TableIdentifier("table_name", None) | ||
| val expected1_table = AlterTableDropPartitionCommand( | ||
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| val expected1_table = AlterTableDropPartitionCommand.fromSpecs( |
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Can you add tests case to check if the parser can accept the comparators added by this pr?
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sure, will do, thanks.
| import org.apache.spark.sql.catalyst.catalog._ | ||
| import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec | ||
| import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference} | ||
| import org.apache.spark.sql.catalyst.expressions._ |
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too many imports?
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not sure what you mean here. The list of imports would be very long, as I use, EqualTo, And, Literal, Cast, BinaryComparison, etc. I can list all them, but I am not sure it is worth. What do you think?
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I just wanted to check if your IDE wrongly folded this import, or not. It's ok.
| ctx.dropPartitionVal().asScala.map { pFilter => | ||
| if (pFilter.identifier() == null || pFilter.constant() == null || | ||
| pFilter.comparisonOperator() == null) { | ||
| throw new ParseException(s"Invalid partition spec: ${pFilter.getText}", ctx) |
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Can you add tests for this exception in DDLParserSuite.scala?
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sure, will do ASAP, thanks.
| ctx: DropPartitionSpecContext): Seq[Expression] = { | ||
| withOrigin(ctx) { | ||
| ctx.dropPartitionVal().asScala.map { pFilter => | ||
| if (pFilter.identifier() == null || pFilter.constant() == null || |
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no chance pFilter.identifier() == null?
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I am not sure. The other 2 conditions can definitely be true, but I am not sure about this. I think it is safer to check it.
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I saw no null check in the other partition spec, then I thought so; https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala#L274
| // running the command. The type is not relevant, it is replaced during the real resolution | ||
| val partition = | ||
| AttributeReference(pFilter.identifier().getText, StringType)() | ||
| val value = Literal(visitStringConstant(pFilter.constant())) |
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val value = Literal(visitStringConstant(pFilter.constant()), StringType) for better readablilty?
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thanks, will update
sorry, I'd need to do Literal.create(visitStringConstant(pFilter.constant()), StringType). Everywhere else here we are using Literal and not Literal.create. So I am not sure it makes sense to change it, but I have not a strong opinion on this. If you prefer, I can switch to Literal.create. Thanks.
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ok, thanks for the check. It's ok to keep the current one.
| // We cannot use UnresolvedAttribute because resolution is performed after Analysis, when | ||
| // running the command. The type is not relevant, it is replaced during the real resolution | ||
| val partition = | ||
| AttributeReference(pFilter.identifier().getText, StringType)() |
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Looks weird and why can we use UnresolvedAttribute in #19691?
https://github.com/apache/spark/pull/19691/files#diff-9847f5cef7cf7fbc5830fbc6b779ee10R293
(Sorry, but probably I miss something?)
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Well, the answer is in def expressions in QueryPlan. In #19691, we end up with a Seq[(TablePartitionSpec, Seq[Expression])], so the expressions there are not recognized/considered by the Analyzer. In this PR we have Seq[Expression] (which is way cleaner IMHO and address comment https://github.com/apache/spark/pull/19691/files#r193002268), so these expressions are considered by the Analyzer.
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Let me have more time to check this behaviour.
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For example, how about this approach? (you tried already?) 52506f1
It added unresolved a logical plan (an input relation and filters) for AlterTableDropPartitionCommand, then resolved the plan in AlterTableDropPartitionCommand.run and computed partition specs based on the resolved expressions?
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Your approach has the same issue, ie. would fail because the LogicalPlan you added is not resolved after analysis.
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I may be missing something here, so sorry if I am not understanding something, but I think the issue is that the analyzer is called anyway before the AlterTableDropPartitionCommand.run command and it fails because of the unresolved attributes. Moreover, in your code I don't see it being part neither of children nor of innerChildren.
I think the alternative here is to add a rule to the analyzer for this, but it seems an overkill to me.
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yea, if you put Expression in the class fields of AlterTableDropPartitionCommand (https://github.com/apache/spark/pull/20999/files#diff-54979ed5797b4a6193cf663dc23baca5R524), it fails in Analyzer.executeAndCheck. But, if we put LogicalPlan in the class fields, IIUC it doesn't fail there.
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oh, now I see, sorry. What about then having a Seq[Filter] instead? In order to avoid the splitDisjunctivePredicates?
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Ya, looks good to me. But, I'm not sure which one is the right approach, so we'd be better to wait for other reviewer's comments here, too. cc: @gatorsmile @viirya
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sure, thanks @maropu.
| * - Less then or Equal: '<=' | ||
| * - Greater than: '>' | ||
| * - Greater then or Equal: '>=' | ||
| */ |
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Hive also supports all the comparators above?
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yes, it does
mgaido91
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Thanks for your comments @maropu. I'll update the PR accordingly asap.
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| dropPartitionVal | ||
| : identifier (comparisonOperator constant)? |
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Hive does throw an error in that case, you mean asking that error is a parsing or another kind of exception?
| ctx: DropPartitionSpecContext): Seq[Expression] = { | ||
| withOrigin(ctx) { | ||
| ctx.dropPartitionVal().asScala.map { pFilter => | ||
| if (pFilter.identifier() == null || pFilter.constant() == null || |
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I am not sure. The other 2 conditions can definitely be true, but I am not sure about this. I think it is safer to check it.
| ctx.dropPartitionVal().asScala.map { pFilter => | ||
| if (pFilter.identifier() == null || pFilter.constant() == null || | ||
| pFilter.comparisonOperator() == null) { | ||
| throw new ParseException(s"Invalid partition spec: ${pFilter.getText}", ctx) |
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sure, will do ASAP, thanks.
| // We cannot use UnresolvedAttribute because resolution is performed after Analysis, when | ||
| // running the command. The type is not relevant, it is replaced during the real resolution | ||
| val partition = | ||
| AttributeReference(pFilter.identifier().getText, StringType)() |
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Well, the answer is in def expressions in QueryPlan. In #19691, we end up with a Seq[(TablePartitionSpec, Seq[Expression])], so the expressions there are not recognized/considered by the Analyzer. In this PR we have Seq[Expression] (which is way cleaner IMHO and address comment https://github.com/apache/spark/pull/19691/files#r193002268), so these expressions are considered by the Analyzer.
| // running the command. The type is not relevant, it is replaced during the real resolution | ||
| val partition = | ||
| AttributeReference(pFilter.identifier().getText, StringType)() | ||
| val value = Literal(visitStringConstant(pFilter.constant())) |
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thanks, will update
sorry, I'd need to do Literal.create(visitStringConstant(pFilter.constant()), StringType). Everywhere else here we are using Literal and not Literal.create. So I am not sure it makes sense to change it, but I have not a strong opinion on this. If you prefer, I can switch to Literal.create. Thanks.
| * - Less then or Equal: '<=' | ||
| * - Greater than: '>' | ||
| * - Greater then or Equal: '>=' | ||
| */ |
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yes, it does
| import org.apache.spark.sql.catalyst.catalog._ | ||
| import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec | ||
| import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference} | ||
| import org.apache.spark.sql.catalyst.expressions._ |
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not sure what you mean here. The list of imports would be very long, as I use, EqualTo, And, Literal, Cast, BinaryComparison, etc. I can list all them, but I am not sure it is worth. What do you think?
| val tableIdent = TableIdentifier("table_name", None) | ||
| val expected1_table = AlterTableDropPartitionCommand( | ||
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| val expected1_table = AlterTableDropPartitionCommand.fromSpecs( |
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sure, will do, thanks.
| test("SPARK-14922: Partition filter is not allowed in ADD PARTITION") { | ||
| withTable("sales") { | ||
| sql("CREATE TABLE sales(id INT) PARTITIONED BY (country STRING, quarter STRING)") | ||
| intercept[AnalysisException] { |
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ok, will do
| */ | ||
| case class PartitioningAttribute(name: String) | ||
| extends Attribute with Unevaluable { | ||
| override val exprId: ExprId = NamedExpression.newExprId |
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even it's a fake attribute, we should not change the exprId when this expression gets copied. Can we move exprId to the constructor?
| // Not really needed and used. We just need a dataType to be used during analysis for resolving | ||
| // the expressions. The String type is used because all the literals in PARTITION operations are | ||
| // parsed as strings and eventually casted later. | ||
| override def dataType: DataType = StringType |
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If it's not needed, can we throw exception here? We may need to override toString though.
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Probably I should improve the comment then. it's misleading: this is actually needed because otherwise we may hit exceptions since the dataType is checked when running checkInputDataTypes of the comparison operator containing it. I'll improve the comment.
| * Create a partition specification map with filters. | ||
| */ | ||
| override def visitDropPartitionSpec( | ||
| ctx: DropPartitionSpecContext): Seq[Expression] = { |
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nit: can we move withOrigin(ctx) here? i.e.
def xxx(): T = withOrigin(ctx) {
...
}
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| } | ||
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| catalog.dropPartitions( |
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does hive have an API to drop partitions with a predicate? I think the current approach is very inefficient with non-equal partition predicates.
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unfortunately, no. I checked https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/metadata/Hive.java but I could find none.
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So the implementation here is similar to how hive implements it?
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Yes, this is my understanding. You can check DDLTaks.dropPartitions.
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retest this please |
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Test build #97389 has finished for PR 20999 at commit
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Test build #97382 has finished for PR 20999 at commit
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Test build #97398 has finished for PR 20999 at commit
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any more comments @cloud-fan @maropu @viirya ? |
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It seems like Hive can drop partitions directly with a partition expression: https://github.com/apache/hive/blob/master/standalone-metastore/metastore-server/src/test/java/org/apache/hadoop/hive/metastore/HiveMetaStoreClientPreCatalog.java#L1016 can you double check this part? |
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Yes, you're right @cloud-fan. I missed that, thanks. I am going to update this with the required change, but it is going to be a huge change. Thanks. |
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@cloud-fan I checked the feasibility of doing what you suggested, but unfortunately that method is very hard to be used (and I am not sure how safe it is). The main issues are:
I am not sure if then we can go ahead with this solution, even though it is suboptimal and eventually create a new ticket for leveraging the Hive metastore API you mentioned in a separate PR, as it is not going to be trivial to do that. What do you think? |
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@mgaido91 |
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thanks fir your comment @jinxing64. I am waiting for an answer for the question above. Currently it is a sub-optimal solution, but I think we can go ahead with it as the Hive API is quite hard to be used, so I'd consider the comment by @cloud-fan as an optimization to be done in a followup PR. If committers can help providing their opinion on this and keeping in review on this, I am active on this PR and it is my goal as well to make this in for 3.0. |
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Is there any progress? @mgaido91 @cloud-fan |
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I am waiting for committers' opinion on the topic above... |
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Test build #107795 has finished for PR 20999 at commit
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Test build #107939 has finished for PR 20999 at commit
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Test build #107940 has finished for PR 20999 at commit
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Is there any progress? @mgaido91 @cloud-fan |
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@mgaido91 @cloud-fan Thanks working on this, this PR has NOT been updated for a long time, i have some ideas to solve the above question in #26280, PTAL and kindly review. |
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We're closing this PR because it hasn't been updated in a while. This isn't a judgement on the merit of the PR in any way. It's just a way of keeping the PR queue manageable. |
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| override lazy val canonicalized: Expression = this.copy(exprId = ExprId(0)) | ||
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| override def withExprId(newExprId: ExprId): Attribute = throw new UnsupportedOperationException |
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override def sql: String = name
Can make the error message more clear.
| sparkSession.sessionState.conf.resolver) :: Nil | ||
| } | ||
| } | ||
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Should check resolvedSpecs here to throw error message if total resolved spec is empty.
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@viirya Any more suggestion on this function? It's really useful for warehouse with so many partition. |
What changes were proposed in this pull request?
Hive has been supporting for a while the ability of dropping partitions using any kind of comparison operator on them. Spark so far is supporting only dropping partitions by exact values. For instance, Spark doesn't support:
The PR adds the support to this syntax too.
The PR takes input from the effort in #19691 by @DazhuangSu. As such, this closes #19691.
How was this patch tested?
UTs to be added