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https://issues.apache.org/jira/browse/HIVE-25975?focusedWorklogId=734654&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-734654
]
ASF GitHub Bot logged work on HIVE-25975:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 01/Mar/22 14:59
Start Date: 01/Mar/22 14:59
Worklog Time Spent: 10m
Work Description: marton-bod commented on a change in pull request #3060:
URL: https://github.com/apache/hive/pull/3060#discussion_r816848964
##########
File path: ql/src/java/org/apache/hadoop/hive/ql/parse/SemanticAnalyzer.java
##########
@@ -8128,13 +8128,9 @@ private FileSinkDesc createFileSinkDesc(String dest,
TableDesc table_desc,
// Some non-native tables might be partitioned without partition spec
information being present in the Table object
HiveStorageHandler storageHandler = dest_tab.getStorageHandler();
if (storageHandler != null && storageHandler.alwaysUnpartitioned()) {
- List<PartitionTransformSpec> nonNativePartSpecs =
storageHandler.getPartitionTransformSpec(dest_tab);
- if (dpCtx == null && nonNativePartSpecs != null &&
!nonNativePartSpecs.isEmpty()) {
- verifyDynamicPartitionEnabled(conf, qb, dest);
- Map<String, String> partSpec = new LinkedHashMap<>();
- nonNativePartSpecs.forEach(ps -> partSpec.put(ps.getColumnName(),
null));
- dpCtx = new DynamicPartitionCtx(partSpec,
conf.getVar(HiveConf.ConfVars.DEFAULTPARTITIONNAME),
-
conf.getIntVar(HiveConf.ConfVars.DYNAMICPARTITIONMAXPARTSPERNODE));
+ DynamicPartitionCtx nonNativeDpCtx =
storageHandler.createDPContext(conf, dest_tab);
+ if (dpCtx == null && nonNativeDpCtx != null) {
Review comment:
This means `dpCtx` does not get initialized at this point for Iceberg
queries?
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Issue Time Tracking
-------------------
Worklog Id: (was: 734654)
Time Spent: 3.5h (was: 3h 20m)
> Optimize ClusteredWriter for bucketed Iceberg tables
> ----------------------------------------------------
>
> Key: HIVE-25975
> URL: https://issues.apache.org/jira/browse/HIVE-25975
> Project: Hive
> Issue Type: Improvement
> Reporter: Ádám Szita
> Assignee: Ádám Szita
> Priority: Major
> Labels: pull-request-available
> Time Spent: 3.5h
> Remaining Estimate: 0h
>
> The first version of the ClusteredWriter in Hive-Iceberg will be lenient for
> bucketed tables: i.e. the records do not need to be ordered by the bucket
> values, the writer will just close its current file and open a new one for
> out-of-order records.
> This is suboptimal for the long-term due to creating many small files. Spark
> uses a UDF to compute the bucket value for each record and therefore it is
> able to order the records by bucket values, achieving optimal clustering.
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