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thanks, merging to master/2.4!
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* @since 2.4.0
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LGTM
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if we are ok with this direction, this LGTM except a few minor comments.
Thanks!
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--- Diff: python/pyspark/sql/functions.py ---
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.. versionchanged:: 3.0
It
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LGTM too
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[SPARK-25846][SQL][TEST] Refactor ExternalAppendOnlyUnsafeRowArrayBenchmark
to use main method
## What changes were proposed in this pull request?
use spark-submit:
bin/spark-submit
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--- Diff: docs/sql-data-sources-avro.md ---
@@ -177,6 +180,19 @@ Data source options of Avro can be set using the
`.option` method on `DataFrameR
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thanks, merging to master!
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@WangTaoTheTonic @cloud-fan @xuanyuanking
I have removed the stream keyword. Table API is supoorted in SQLStreaming
now.
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In fact, `BinaryFileRDD ` uses `max(defaultParallelism, minPartitions)`:
`BinaryFileRDD --->setMinPartitions--->Math.max(sc.defaultParallelism,
minPartitions)`.
In addition, for this
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--- Diff: docs/sql-data-sources-avro.md ---
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Nice catch! LGTM
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LGTM too
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Looks good to me.
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--- Diff: python/pyspark/sql/window.py ---
@@ -239,34 +212,27 @@ def rangeBetween(self, start, end):
and "5" means the five off after the
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--- Diff: python/pyspark/sql/window.py ---
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and "5" means the five off after the current
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--- Diff: R/pkg/R/SQLContext.R ---
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#' Loads a Parquet file, returning the result as a
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and "5" means the five off after the
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This can be easily worked around, no?
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Yup, I also agree with this revert.
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I agree it should be a literal value.
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Maybe I am too much careful about it but I am kind of nervous about this
column case. I don't intend to disallow it entirely but only for Spark 2.4. We
might have to find a way to use column
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Actually, that usecase can more easily accomplished by simply inferring
schema by JSON datasource. Yea, I indeed suggested that as workaround for this
issue before. Let's say,
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