[英]GCP Dataflow Apache Beam code logic not working as expected
I am trying to implement a CDC in Apache Beam, deployed in Google Cloud Dataflow.我正在尝试在 Apache Beam 中实现 CDC,部署在 Google Cloud Dataflow 中。
I have unloaded the master data and the new data, which is expected to coming daily.我已经卸载了主数据和新数据,预计每天都会出现。 The join is not working as expected.
联接未按预期工作。 Something is missing.
缺了点什么。
master_data = (
p | 'Read base from BigQuery ' >> beam.io.Read(beam.io.BigQuerySource(query=master_data, use_standard_sql=True))
| 'Map id in master' >> beam.Map(lambda master: (
master['id'], master)))
new_data = (
p | 'Read Delta from BigQuery ' >> beam.io.Read(beam.io.BigQuerySource(query=new_data, use_standard_sql=True))
| 'Map id in new' >> beam.Map(lambda new: (new['id'], new)))
joined_dicts = (
{'master_data' :master_data, 'new_data' : new_data }
| beam.CoGroupByKey()
| beam.FlatMap(join_lists)
| 'mergeddicts' >> beam.Map(lambda masterdict, newdict: newdict.update(masterdict))
)
def join_lists(k,v):
itertools.product(v['master_data'], v['new_data'])
Observations (on sample data):观察结果(对样本数据):
Data from the master来自主人的数据
1, 'A',3232
2, 'B',234
New Data:新数据:
1,'A' ,44
4,'D',45
Expected result in master table, post the code implementation:主表中的预期结果,贴出代码实现:
1, 'A',44
2, 'B',234
4,'D',45
However, what I am getting in master table is:但是,我在主表中得到的是:
1,'A' ,44
4,'D',45
Am I missing a step?我错过了一步吗? Can anyone please assist in rectifying my mistake.
任何人都可以帮助纠正我的错误。
You don't need to flatten after group by as it separates the elements again.您不需要在分组后展平,因为它会再次分隔元素。
Here is the sample code.这是示例代码。
from apache_beam.options.pipeline_options import PipelineOptions
import apache_beam as beam
def join_lists(e):
(k,v)=e
return (k, v['new_data']) if v['new_data'] != v['master_data'] else (k, None)
with beam.Pipeline(options=PipelineOptions()) as p:
master_data = (
p | 'Read base from BigQuery ' >> beam.Create([('A', [3232]),('B', [234])])
)
new_data = (
p | 'Read Delta from BigQuery ' >> beam.Create([('A',[44]),('D',[45])])
)
joined_dicts = (
{'master_data' :master_data, 'new_data' : new_data }
| beam.CoGroupByKey()
| 'mergeddicts' >> beam.Map(join_lists)
)
result = p.run()
result.wait_until_finish()
print("Pipeline finished.")
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