rdblue commented on a change in pull request #23622: [SPARK-26677][SQL] Disable
dictionary filtering by default at Parquet
URL: https://github.com/apache/spark/pull/23622#discussion_r251248759
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala
##########
@@ -314,6 +314,17 @@ class ParquetFileFormat
SQLConf.CASE_SENSITIVE.key,
sparkSession.sessionState.conf.caseSensitiveAnalysis)
+ // There are two things to note here.
+ //
+ // 1. Dictionary filtering has an issue about the predication on null. For
this reason,
+ // This filtering is disabled. See SPARK-26677.
+ //
+ // 2. We should disable 'parquet.filter.dictionary.enabled' but
+ // the 'parquet.filter.stats.enabled' and
'parquet.filter.dictionary.enabled' were
+ // swapped mistakenly in Parquet side. It should use
'parquet.filter.dictionary.enabled'
+ // when Spark upgrades Parquet. See PARQUET-1309.
+ hadoopConf.setIfUnset(ParquetInputFormat.STATS_FILTERING_ENABLED, "false")
Review comment:
Dictionary filtering has been available for more than 2 years and Netflix
has been using it by default for almost 3 years without problems. The feature
is stable.
Keep in mind what a narrow use case hits this bug. First, an entire row
group in a file needs to have a just one value and nulls: either the column has
just one non-null value for all rows, or a sort or write pattern has clustered
null rows with one other value (enough for an entire row group). Next, a query
must use null-safe equality *and* negate it. In my experience, most people
don't know what null-safe equality is. Going back to the use cases that produce
data like this, the first use case -- only one non-null value -- would probably
result in filter like `col NOT NULL` instead. The second write pattern is the
problematic one, but how likely is the intersection of data with that write
pattern and searching for all values except one with null-safe equality? I
don't think it is likely and I think that's why we haven't found this until now.
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