使用 DataFlow PubSub 到 Cloud Storage 很慢

Question

I am using a slightly adjusted version of the following example snippet to write PubSub messages to GCS:

 class WriteToGCS(beam.DoFn): def __init__(self, output_path, prefix): self.output_path = output_path self.prefix = prefix def process(self, key_value, window=beam.DoFn.WindowParam): """Write messages in a batch to Google Cloud Storage.""" start_date = window.start.to_utc_datetime().date().isoformat() start = window.start.to_utc_datetime().isoformat() end = window.end.to_utc_datetime().isoformat() shard_id, batch = key_value filename = f'{self.output_path}/{start_date}/{start}-{end}/{self.prefix}-{start}-{end}-{shard_id:03d}' with beam.io.gcsio.GcsIO().open(filename=filename, mode="w") as f: for message_body in batch: f.write(f"{message_body},".encode("utf-8"))

However, its terribly slow. This is how it looks like in the graph . Is there a way to speed up this step? The subscription gets 500 elements per second, so 3-10 elements per seconds is not keeping up.

The pipeline looks like this:

 class JsonWriter(beam.PTransform): def __init__(self, window_size, path, prefix, num_shards=20): self.window_size = int(window_size) self.path = path self.prefix = prefix self.num_shards = num_shards def expand(self, pcoll): return ( pcoll | "Group into fixed windows" >> beam.WindowInto(window.FixedWindows(self.window_size, 0)) | "Decode windowed elements" >> beam.ParDo(Decode()) | "Group into batches" >> beam.BatchElements() | "Add key" >> beam.WithKeys(lambda _: random.randint(0, int(self.num_shards) - 1)) | "Write to GCS" >> beam.ParDo(WriteToGCS(self.path, self.prefix)) )

Answer 1

Solved this with these steps:

 | "Add Path" >> beam.ParDo(AddFilename(self.path, self.prefix, self.num_shards)) | "Group Paths" >> beam.GroupByKey() | "Join and encode" >> beam.ParDo(ToOneString()) | "Write to GCS" >> beam.ParDo(WriteToGCS())

First I add the paths per element, then I group by path (to prevent simultaneous writes to the same file/shard). Then I concatenate (new line delimited) the JSON strings per group (path) and then write the whole string to the file. This reduces the calls to GCS tremendously, since I dont write every element one by one to a file, but instead join them first and then write once. Hope it helps someone.