我正在尝试编写一个自定义模板以读取CSV并将其输出到另一个CSV。目的是在此CSV中选择所需的数据。当我在网络界面上运行它时,出现以下错误
我已尽可能减少代码以了解我的错误,但我仍然看不到它。 我帮助自己制作了文档:https://cloud.google.com/dataflow/docs/guides/templates/creating-templates#creating-and-staging-templates
class UploadOptions(PipelineOptions):
@classmethod
def _add_argparse_args(cls, parser):
parser.add_value_provider_argument(
'--input',
default='gs://[MYBUCKET]/input.csv',
help='Path of the file to read from')
parser.add_value_provider_argument(
'--output',
required=True,
help='Output file to write results to.')
pipeline_options = PipelineOptions(['--output', 'gs://[MYBUCKET]/output'])
p = beam.Pipeline(options=pipeline_options)
upload_options = pipeline_options.view_as(UploadOptions)
(p
| 'read' >> beam.io.Read(upload_options.input)
| 'Write' >> beam.io.WriteToText(upload_options.output, file_name_suffix='.csv'))
当前错误如下
无法解析文件'gs://MYBUCKET/template.py'。
在终端中,我遇到以下错误
错误:(gcloud.dataflow.jobs.run)失败:无法解析模板文件“ gs:// [MYBUCKET] /template.py”。 -'@type':type.googleapis.com/google.rpc.PreconditionFailure 违规: -描述:“流的意外末尾:预期的'{'” 主题:0:0 类型:JSON
提前谢谢
答案 0 :(得分:1)
我设法解决了我的问题。问题来自我在管道读取中使用的变量。 custom_options变量必须在Read中使用,而不是known_args变量
custom_options = pipeline_options.view_as(CustomPipelineOptions)
我编写了通用代码,如果有人需要,我会分享我的解决方案。
from __future__ import absolute_import
import argparse
import apache_beam as beam
from apache_beam.io import ReadFromText
from apache_beam.io import WriteToText
from apache_beam.metrics.metric import MetricsFilter
from apache_beam.options.pipeline_options import PipelineOptions, GoogleCloudOptions, SetupOptions
class CustomPipelineOptions(PipelineOptions):
"""
Runtime Parameters given during template execution
path and organization parameters are necessary for execution of pipeline
campaign is optional for committing to bigquery
"""
@classmethod
def _add_argparse_args(cls, parser):
parser.add_value_provider_argument(
'--path',
type=str,
help='Path of the file to read from')
parser.add_value_provider_argument(
'--output',
type=str,
help='Output file if needed')
def run(argv=None):
parser = argparse.ArgumentParser()
known_args, pipeline_args = parser.parse_known_args(argv)
global cloud_options
global custom_options
pipeline_options = PipelineOptions(pipeline_args)
cloud_options = pipeline_options.view_as(GoogleCloudOptions)
custom_options = pipeline_options.view_as(CustomPipelineOptions)
pipeline_options.view_as(SetupOptions).save_main_session = True
p = beam.Pipeline(options=pipeline_options)
init_data = (p
| 'Hello World' >> beam.Create(['Hello World'])
| 'Read Input path' >> beam.Read(custom_options.path)
)
result = p.run()
# result.wait_until_finish
if __name__ == '__main__':
run()
然后启动以下命令以在GCP上生成模板
python template.py --runner DataflowRunner --project $PROJECT --staging_location gs://$BUCKET/staging --temp_location gs://$BUCKET/temp --
template_location gs://$BUCKET/templates/$TemplateName