Parallelize encoding of a single row #546
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Fields that contain data that is not natively supported by Parqyet format, such as numpy arrays, are serialized into byte arrays. Images maybe compressed using png or jpeg compression. Serializing fields on a thread pool speeds up this process in some cases (e.g. a row contains multiple images). This PR adds a pool executor argument to `dict_to_spark_row` enabling user to pass a pool executor that would be used for parallelizing this serialization. If no pool executor is specified, the encoding/serialization is performed on the caller thread.
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Codecov ReportBase: 82.88% // Head: 85.99% // Increases project coverage by
Additional details and impacted files@@ Coverage Diff @@
## master #546 +/- ##
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+ Coverage 82.88% 85.99% +3.11%
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Files 85 87 +2
Lines 4721 4935 +214
Branches 744 783 +39
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+ Hits 3913 4244 +331
+ Misses 678 568 -110
+ Partials 130 123 -7
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When writing data into a petastorm dataset. Before a pyspark sql.Row
object is created, fields containing data that is not natively supported
by Parqyet format, such as numpy arrays, are serialized into byte
arrays. Images maybe compressed using png or jpeg compression.
Serializing fields on a thread pool speeds up this process in some
cases (e.g. a row contains multiple images).