I have got a pipeline that parses records from AVRO files.
我有一个解析AVRO文件记录的管道。
I need to split the incoming records into chunks of 500 items in order to call an API that takes multiple inputs at the same time.
我需要将传入的记录拆分为500个项目的块,以便调用同时接受多个输入的API。
Is there a way to do this with the Python SDK?
有没有办法用Python SDK做到这一点?
1 个解决方案
#1
1
I'm supposing that you mean a Batch use case. You have a couple options for this:
我想你的意思是批用例。你有几个选择:
If your PCollection is large enough, and you have some flexibility on the size of your bundles, you can use a GroupByKey
transform after assigning keys in random/round robin order to your elements. e.g.:
如果你的PCollection足够大,并且你对bundle的大小有一定的灵活性,你可以在以随机/循环方式为你的元素分配键后使用GroupByKey转换。例如。:
my_collection = p | ReadRecordsFromAvro()
element_bundles = (my_collection
# Choose a number of keys that works for you (I chose 50 here)
| 'AddKeys' >> beam.Map(lambda x: (randint(0, 50), x))
| 'MakeBundles' >> beam.GroupByKey()
| 'DropKeys' >> beam.Map(lambda (k, bundle): bundle)
| beam.ParDo(ProcessBundlesDoFn()))
Where ProcessBundlesDoFn
is something like so:
ProcessBundlesDoFn就是这样的:
class ProcessBundlesDoFn(beam.DoFn):
def process(self, bundle):
while bundle.has_next():
# Fetch in batches of 500 until you're done
result = fetch_n_elements(bundle, 500)
yield result
If you need to have all bundles of exactly 500 elements, then you may need to:
如果您需要包含恰好500个元素的所有包,那么您可能需要:
- Count the # of elements in your PCollection
- 计算PCollection中的元素数量
- Pass that count as a singleton side input to your
'AddKeys'
ParDo, to determine exactly the number of keys that you will need. - 将该计数作为单一侧输入传递给您的“AddKeys”ParDo,以确切确定您需要的键数。
Hope that helps.
希望有所帮助。
#1
1
I'm supposing that you mean a Batch use case. You have a couple options for this:
我想你的意思是批用例。你有几个选择:
If your PCollection is large enough, and you have some flexibility on the size of your bundles, you can use a GroupByKey
transform after assigning keys in random/round robin order to your elements. e.g.:
如果你的PCollection足够大,并且你对bundle的大小有一定的灵活性,你可以在以随机/循环方式为你的元素分配键后使用GroupByKey转换。例如。:
my_collection = p | ReadRecordsFromAvro()
element_bundles = (my_collection
# Choose a number of keys that works for you (I chose 50 here)
| 'AddKeys' >> beam.Map(lambda x: (randint(0, 50), x))
| 'MakeBundles' >> beam.GroupByKey()
| 'DropKeys' >> beam.Map(lambda (k, bundle): bundle)
| beam.ParDo(ProcessBundlesDoFn()))
Where ProcessBundlesDoFn
is something like so:
ProcessBundlesDoFn就是这样的:
class ProcessBundlesDoFn(beam.DoFn):
def process(self, bundle):
while bundle.has_next():
# Fetch in batches of 500 until you're done
result = fetch_n_elements(bundle, 500)
yield result
If you need to have all bundles of exactly 500 elements, then you may need to:
如果您需要包含恰好500个元素的所有包,那么您可能需要:
- Count the # of elements in your PCollection
- 计算PCollection中的元素数量
- Pass that count as a singleton side input to your
'AddKeys'
ParDo, to determine exactly the number of keys that you will need. - 将该计数作为单一侧输入传递给您的“AddKeys”ParDo,以确切确定您需要的键数。
Hope that helps.
希望有所帮助。