def test_replace_single_pcoll_token(self):
sql = 'SELECT * FROM abc WHERE a=1 AND b=2'
replaced_sql = replace_single_pcoll_token(sql, 'wow')
self.assertEqual(replaced_sql, sql)
replaced_sql = replace_single_pcoll_token(sql, 'abc')
self.assertEqual(replaced_sql,
'SELECT * FROM PCOLLECTION WHERE a=1 AND b=2')
def _build_query_components(
query: str,
found: Dict[str, beam.PCollection],
output_name: str,
run: bool = True
) -> Tuple[str,
Union[Dict[str, beam.PCollection], beam.PCollection, beam.Pipeline],
SqlChain]:
"""Builds necessary components needed to apply the SqlTransform.
Args:
query: The SQL query to be executed by the magic.
found: The PCollections with variable names found to be used by the query.
output_name: The output variable name in __main__ module.
run: Whether to prepare components for a local run or not.
Returns:
The processed query to be executed by the magic; a source to apply the
SqlTransform to: a dictionary of tagged PCollections, or a single
PCollection, or the pipeline to execute the query; the chain of applied
beam_sql magics this one belongs to.
"""
if found:
user_pipeline = ie.current_env().user_pipeline(
next(iter(found.values())).pipeline)
sql_pipeline = beam.Pipeline(options=user_pipeline._options)
ie.current_env().add_derived_pipeline(user_pipeline, sql_pipeline)
sql_source = {}
if run:
if has_source_to_cache(user_pipeline):
sql_source = pcolls_from_streaming_cache(
user_pipeline, sql_pipeline, found)
else:
cache_manager = ie.current_env().get_cache_manager(
user_pipeline, create_if_absent=True)
for pcoll_name, pcoll in found.items():
cache_key = CacheKey.from_pcoll(pcoll_name, pcoll).to_str()
sql_source[pcoll_name] = unreify_from_cache(
pipeline=sql_pipeline,
cache_key=cache_key,
cache_manager=cache_manager,
element_type=pcoll.element_type)
else:
sql_source = found
if len(sql_source) == 1:
query = replace_single_pcoll_token(query, next(iter(sql_source.keys())))
sql_source = next(iter(sql_source.values()))
node = SqlNode(
output_name=output_name, source=set(found.keys()), query=query)
chain = ie.current_env().get_sql_chain(
user_pipeline, set_user_pipeline=True).append(node)
else: # does not query any existing PCollection
sql_source = beam.Pipeline()
ie.current_env().add_user_pipeline(sql_source)
# The node should be the root node of the chain created below.
node = SqlNode(output_name=output_name, source=sql_source, query=query)
chain = ie.current_env().get_sql_chain(sql_source).append(node)
return query, sql_source, chain
def _build_query_components(
query: str, found: Dict[str, beam.PCollection]
) -> Tuple[str, Union[Dict[str, beam.PCollection], beam.PCollection,
beam.Pipeline]]:
"""Builds necessary components needed to apply the SqlTransform.
Args:
query: The SQL query to be executed by the magic.
found: The PCollections with variable names found to be used by the query.
Returns:
The processed query to be executed by the magic and a source to apply the
SqlTransform to: a dictionary of tagged PCollections, or a single
PCollection, or the pipeline to execute the query.
"""
if found:
user_pipeline = ie.current_env().user_pipeline(
next(iter(found.values())).pipeline)
sql_pipeline = beam.Pipeline(options=user_pipeline._options)
ie.current_env().add_derived_pipeline(user_pipeline, sql_pipeline)
sql_source = {}
if has_source_to_cache(user_pipeline):
sql_source = pcolls_from_streaming_cache(user_pipeline,
sql_pipeline, found)
else:
cache_manager = ie.current_env().get_cache_manager(
user_pipeline, create_if_absent=True)
for pcoll_name, pcoll in found.items():
cache_key = CacheKey.from_pcoll(pcoll_name, pcoll).to_str()
sql_source[pcoll_name] = unreify_from_cache(
pipeline=sql_pipeline,
cache_key=cache_key,
cache_manager=cache_manager,
element_type=pcoll.element_type)
if len(sql_source) == 1:
query = replace_single_pcoll_token(query,
next(iter(sql_source.keys())))
sql_source = next(iter(sql_source.values()))
else:
sql_source = beam.Pipeline()
ie.current_env().add_user_pipeline(sql_source)
return query, sql_source
def _build_query_components(
query: str, found: Dict[str, beam.PCollection]
) -> Tuple[str, Union[Dict[str, beam.PCollection], beam.PCollection,
beam.Pipeline]]:
"""Builds necessary components needed to apply the SqlTransform.
Args:
query: The SQL query to be executed by the magic.
found: The PCollections with variable names found to be used by the query.
Returns:
The processed query to be executed by the magic and a source to apply the
SqlTransform to: a dictionary of tagged PCollections, or a single
PCollection, or the pipeline to execute the query.
"""
if found:
user_pipeline = next(iter(found.values())).pipeline
cache_manager = ie.current_env().get_cache_manager(user_pipeline)
instrumentation = inst.build_pipeline_instrument(user_pipeline)
sql_pipeline = beam.Pipeline(options=user_pipeline._options)
ie.current_env().add_derived_pipeline(user_pipeline, sql_pipeline)
sql_source = {}
if instrumentation.has_unbounded_sources:
sql_source = pcolls_from_streaming_cache(user_pipeline,
sql_pipeline, found,
instrumentation,
cache_manager)
else:
for pcoll_name, pcoll in found.items():
cache_key = instrumentation.cache_key(pcoll)
sql_source[pcoll_name] = pcoll_from_file_cache(
sql_pipeline, pcoll, cache_manager, cache_key)
if len(sql_source) == 1:
query = replace_single_pcoll_token(query,
next(iter(sql_source.keys())))
sql_source = next(iter(sql_source.values()))
else:
sql_source = beam.Pipeline()
return query, sql_source