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Posted to commits@hudi.apache.org by GitBox <gi...@apache.org> on 2022/07/25 14:55:28 UTC
[GitHub] [hudi] yihua commented on a diff in pull request #5746: [HUDI-4250][HUDI-4202] Optimize performance of Column Stats Index reading in Data Skipping
yihua commented on code in PR #5746:
URL: https://github.com/apache/hudi/pull/5746#discussion_r928972329
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hudi-common/src/main/java/org/apache/hudi/BaseHoodieTableFileIndex.java:
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@@ -166,6 +167,11 @@ public Map<String, List<FileSlice>> listFileSlices() {
.collect(Collectors.toMap(e -> e.getKey().path, Map.Entry::getValue));
}
+ public int getFileSlicesCount() {
+ return cachedAllInputFileSlices.values().stream()
+ .reduce(0, (count, fileSlices) -> count + fileSlices.size(), Integer::sum);
Review Comment:
This is not quite obvious. Do sth like `cachedAllInputFileSlices.values().stream().mapToInt(List::size).sum()` instead?
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hudi-common/src/main/java/org/apache/hudi/common/config/HoodieMetadataConfig.java:
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@@ -187,6 +187,18 @@ public final class HoodieMetadataConfig extends HoodieConfig {
.sinceVersion("0.11.0")
.withDocumentation("Comma-separated list of columns for which column stats index will be built. If not set, all columns will be indexed");
+ public static final String COLUMN_STATS_INDEX_PROCESSING_MODE_IN_MEMORY = "in-memory";
+ public static final String COLUMN_STATS_INDEX_PROCESSING_MODE_SPARK = "spark";
Review Comment:
nit: this can be enums.
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hudi-common/src/main/java/org/apache/hudi/common/config/HoodieMetadataConfig.java:
##########
@@ -187,6 +187,18 @@ public final class HoodieMetadataConfig extends HoodieConfig {
.sinceVersion("0.11.0")
.withDocumentation("Comma-separated list of columns for which column stats index will be built. If not set, all columns will be indexed");
+ public static final String COLUMN_STATS_INDEX_PROCESSING_MODE_IN_MEMORY = "in-memory";
+ public static final String COLUMN_STATS_INDEX_PROCESSING_MODE_SPARK = "spark";
Review Comment:
`COLUMN_STATS_INDEX_PROCESSING_MODE_SPARK`: based on the logic, this mode is more of leveraging engine context, could be Spark or Flink (plain Java), right?
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