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weather-mv
will ingest data into BQ from Zarr much faster.
#357
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Found a couple of errors with loading a Zarr dataset into BigQuery.
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Overall LGTM.
@dabhicusp / @DarshanSP19, could you please provide the benchmarking results for the current main branch as compared to this specific branch?
paths | ||
| 'OpenChunks' >> xbeam.DatasetToChunks(ds, chunks) | ||
| 'ExtractRows' >> beam.FlatMapTuple(self.chunks_to_rows) | ||
| 'Window' >> beam.WindowInto(window.FixedWindows(60)) |
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LGTM @alxmrs.
Data after running pipelines for mentioned cases.
This changes are relatively fast than before for zarr batch ingestion. |
weather-mv bq
's previous Zarr ingestion system only used one worker. This PR uses Xarray-Beam for Zarr ingestion, in order to distributedxr.Dataset
chunks across beam workers. This improves ingestion into BQ.Outstanding issues: I can't find a way to incrementally load rows into BQ from Zarr. While I've used windowing on fixed intervals to break up a large ingestion job into smaller parts, it seems like the actual writing to BQ gets stuck in a reshuffle step within the
WriteToBigQuery
transform. In this PR or a future PR, let's try to find a way to incrementally write rows to BQ once they've been processed, instead of having to wait for the entire dataset to be processed. CC: @dabhicusp.