我们正在使用 BigQuery Python API 运行一些分析。为此，我们创建了以下适配器:
def stream_data(self, table, data, schema, how=None):
r = self.connector.tables().list(projectId=self._project_id,
datasetId='lbanor').execute()
table_exists = [row['tableReference']['tableId'] for row in
r['tables'] if
row['tableReference']['tableId'] == table]
if table_exists:
if how == 'WRITE_TRUNCATE':
self.connector.tables().delete(projectId=self._project_id,
datasetId='lbanor',
tableId=table).execute()
body = {
'tableReference': {
'tableId': table,
'projectId': self._project_id,
'datasetId': 'lbanor'
},
'schema': schema
}
self.connector.tables().insert(projectId=(
self._project_id),
datasetId='lbanor',
body=body).execute()
else:
body = {
'tableReference': {
'tableId': table,
'projectId': self._project_id,
'datasetId': 'lbanor'
},
'schema': schema
}
self.connector.tables().insert(projectId=(
self._project_id),
datasetId='lbanor',
body=body).execute()
body = {
'rows': [
{
'json': data,
'insertId': str(uuid.uuid4())
}
]
}
self.connector.tabledata().insertAll(projectId=(
self._project_id),
datasetId='lbanor',
tableId=table,
body=body).execute(num_retries=5)
connector 只是构建对象。
它的主要目的是将数据流式传输到给定的表。如果该表已经存在并且“如何”输入作为“WRITE_TRUNCATE”传递，则首先删除并重新创建该表。 之后，继续做数据流。
如果不一遍又一遍地删除表，一切正常。
例如，这是我们在不模拟写截断选项的情况下运行脚本时的结果(for 循环不断调用 stream_data 和 how=None):
[
{
"date": "2016-04-25",
"unix_date": "1461606664981207",
"init_cv_date": "2016-03-12",
"end_cv_date": "2016-03-25",
"days_trained": "56",
"days_validated": "14",
"navigated_score": "1",
"carted_score": "3",
"purchased_score": "10",
"description": "First trial of top seller alg. No filter nor any condition is applied. Skus not present in train count as rank=0.5",
"metric": "rank",
"result": "0.31729249914663893"
},
{
"date": "2016-04-25",
"unix_date": "1461606599745107",
"init_cv_date": "2016-03-06",
"end_cv_date": "2016-03-25",
"days_trained": "80",
"days_validated": "20",
"navigated_score": "1",
"carted_score": "3",
"purchased_score": "10",
"description": "First trial of top seller alg. No filter nor any condition is applied. Skus not present in train count as rank=0.5",
"metric": "rank",
"result": "0.32677143128667446"
},
{
"date": "2016-04-25",
"unix_date": "1461606688950415",
"init_cv_date": "2016-03-14",
"end_cv_date": "2016-03-25",
"days_trained": "48",
"days_validated": "12",
"navigated_score": "1",
"carted_score": "3",
"purchased_score": "10",
"description": "First trial of top seller alg. No filter nor any condition is applied. Skus not present in train count as rank=0.5",
"metric": "rank",
"result": "0.3129267723358932"
},
{
"date": "2016-04-25",
"unix_date": "1461606707195122",
"init_cv_date": "2016-03-16",
"end_cv_date": "2016-03-25",
"days_trained": "40",
"days_validated": "10",
"navigated_score": "1",
"carted_score": "3",
"purchased_score": "10",
"description": "First trial of top seller alg. No filter nor any condition is applied. Skus not present in train count as rank=0.5",
"metric": "rank",
"result": "0.310620987663015"
},
{
"date": "2016-04-25",
"unix_date": "1461606622432947",
"init_cv_date": "2016-03-08",
"end_cv_date": "2016-03-25",
"days_trained": "72",
"days_validated": "18",
"navigated_score": "1",
"carted_score": "3",
"purchased_score": "10",
"description": "First trial of top seller alg. No filter nor any condition is applied. Skus not present in train count as rank=0.5",
"metric": "rank",
"result": "0.32395802949369296"
}
]
但是当我们使用带有输入 how="WRITE_TRUNCATE"的同一个适配器时，它的行为发生了变化并且变得不可预测。
有时它可以工作并且数据被保存到表中。但有时，即使没有出现错误，也没有数据保存到表中。
尝试查询表时，没有返回任何数据。它只返回“查询返回零结果”。
删除表、重新创建表和流式传输数据时出错。我们是不是犯了什么错误？
如果您需要更多信息，请告诉我。提前致谢!
最佳答案
查看 Jordan Tigani 的回答和 Sean Chen 对 https://stackoverflow.com/a/36417177/132438 的评论(均为 BigQuery 工程师)。
总结是:
- 当重新创建或截断表时“您需要等待超过 2 分钟才能进行流式传输，以避免数据被丢弃。
这样就可以解释为什么会出现这种不确定的行为。
关于python - 流式传输前 BigQuery 表截断不起作用，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/36846571/