Added log statement for number of successful ingestions#15
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Added log statement for number of successful ingestions#15
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Added log statement for number of successful ingestions This change adds a counter and log statement for the number of records successfully ingested through online streaming ingestion
can-sun
reviewed
Apr 3, 2023
| ): Iterator[Row] = { | ||
| val newPartition = partition.map(row => { | ||
| // Increment the row counter value | ||
| dataFrameSizeCounter.add(1) |
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Accumulator is not reliable if it is not inside of an action. For our use case, the counter is added to map.
https://stackoverflow.com/questions/29494452/when-are-accumulators-truly-reliable
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Is it viable to seek more reliable way instead?
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This change adds a counter and log statement for the number of records successfully ingested through online streaming ingestion
Description of changes:
Introduced a long accumulator for counting the total number of rows in the spark dataframe and subtracted the number of failed rows to log the successfully ingested rows
Testing done:
Verified through unit tests that the number of successful records are correctly logged
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