Can I issue a query rather than specify a table when using the BigQuery connector for Spark?
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I have used the Use the BigQuery connector with Spark to extract data from a table in BigQuery by running the code on Google Dataproc. As far as I'm aware the code shared there:
conf =
# Input Parameters.
'mapred.bq.project.id': project,
'mapred.bq.gcs.bucket': bucket,
'mapred.bq.temp.gcs.path': input_directory,
'mapred.bq.input.project.id': 'publicdata',
'mapred.bq.input.dataset.id': 'samples',
'mapred.bq.input.table.id': 'shakespeare',
# Output Parameters.
output_dataset = 'wordcount_dataset'
output_table = 'wordcount_output'
# Load data in from BigQuery.
table_data = sc.newAPIHadoopRDD(
'com.google.cloud.hadoop.io.bigquery.JsonTextBigQueryInputFormat',
'org.apache.hadoop.io.LongWritable',
'com.google.gson.JsonObject',
conf=conf)
copies the entirety of the named table into input_directory. The table I need to extract data from contains >500m rows and I don't need all of those rows. Is there a way to instead issue a query (as opposed to specifying a table) so that I can copy a subset of the data from a table?
google-bigquery 
google-cloud-dataproc asked Nov 9 at 13:49
jamiet
2,26212446
add a comment |
up vote
2
down vote
favorite
I have used the Use the BigQuery connector with Spark to extract data from a table in BigQuery by running the code on Google Dataproc. As far as I'm aware the code shared there:
conf =
# Input Parameters.
'mapred.bq.project.id': project,
'mapred.bq.gcs.bucket': bucket,
'mapred.bq.temp.gcs.path': input_directory,
'mapred.bq.input.project.id': 'publicdata',
'mapred.bq.input.dataset.id': 'samples',
'mapred.bq.input.table.id': 'shakespeare',
# Output Parameters.
output_dataset = 'wordcount_dataset'
output_table = 'wordcount_output'
# Load data in from BigQuery.
table_data = sc.newAPIHadoopRDD(
'com.google.cloud.hadoop.io.bigquery.JsonTextBigQueryInputFormat',
'org.apache.hadoop.io.LongWritable',
'com.google.gson.JsonObject',
conf=conf)
copies the entirety of the named table into input_directory. The table I need to extract data from contains >500m rows and I don't need all of those rows. Is there a way to instead issue a query (as opposed to specifying a table) so that I can copy a subset of the data from a table?
google-bigquery google-cloud-dataproc asked Nov 9 at 13:49
jamiet
2,26212446
1
An alternative is to create a temp table then read it with Spark.
– Dagang
Nov 23 at 21:05
add a comment |
up vote
2
down vote
favorite
up vote
2
down vote
favorite
I have used the Use the BigQuery connector with Spark to extract data from a table in BigQuery by running the code on Google Dataproc. As far as I'm aware the code shared there:
conf =
# Input Parameters.
'mapred.bq.project.id': project,
'mapred.bq.gcs.bucket': bucket,
'mapred.bq.temp.gcs.path': input_directory,
'mapred.bq.input.project.id': 'publicdata',
'mapred.bq.input.dataset.id': 'samples',
'mapred.bq.input.table.id': 'shakespeare',
# Output Parameters.
output_dataset = 'wordcount_dataset'
output_table = 'wordcount_output'
# Load data in from BigQuery.
table_data = sc.newAPIHadoopRDD(
'com.google.cloud.hadoop.io.bigquery.JsonTextBigQueryInputFormat',
'org.apache.hadoop.io.LongWritable',
'com.google.gson.JsonObject',
conf=conf)
copies the entirety of the named table into input_directory. The table I need to extract data from contains >500m rows and I don't need all of those rows. Is there a way to instead issue a query (as opposed to specifying a table) so that I can copy a subset of the data from a table?
google-bigquery google-cloud-dataproc asked Nov 9 at 13:49
jamiet
2,26212446
I have used the Use the BigQuery connector with Spark to extract data from a table in BigQuery by running the code on Google Dataproc. As far as I'm aware the code shared there:
conf =
# Input Parameters.
'mapred.bq.project.id': project,
'mapred.bq.gcs.bucket': bucket,
'mapred.bq.temp.gcs.path': input_directory,
'mapred.bq.input.project.id': 'publicdata',
'mapred.bq.input.dataset.id': 'samples',
'mapred.bq.input.table.id': 'shakespeare',
# Output Parameters.
output_dataset = 'wordcount_dataset'
output_table = 'wordcount_output'
# Load data in from BigQuery.
table_data = sc.newAPIHadoopRDD(
'com.google.cloud.hadoop.io.bigquery.JsonTextBigQueryInputFormat',
'org.apache.hadoop.io.LongWritable',
'com.google.gson.JsonObject',
conf=conf)
copies the entirety of the named table into input_directory. The table I need to extract data from contains >500m rows and I don't need all of those rows. Is there a way to instead issue a query (as opposed to specifying a table) so that I can copy a subset of the data from a table?
google-bigquery google-cloud-dataproc google-bigquery google-cloud-dataproc asked Nov 9 at 13:49
jamiet
2,26212446
asked Nov 9 at 13:49
jamiet
2,26212446
asked Nov 9 at 13:49
jamiet
2,26212446
asked Nov 9 at 13:49
jamiet
2,26212446
asked Nov 9 at 13:49
jamiet
2,26212446
2,26212446
1
An alternative is to create a temp table then read it with Spark.
– Dagang
Nov 23 at 21:05
add a comment |
1
An alternative is to create a temp table then read it with Spark.
– Dagang
Nov 23 at 21:05
1
1
An alternative is to create a temp table then read it with Spark.
– Dagang
Nov 23 at 21:05
An alternative is to create a temp table then read it with Spark.
– Dagang
Nov 23 at 21:05
add a comment |
1 Answer
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Doesn't look like BigQuery supports any kind of filtering/querying for tables export at the moment:
https://cloud.google.com/bigquery/docs/exporting-data
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.extract
answered Nov 9 at 15:27
Igor Dvorzhak
624413
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
accepted
Doesn't look like BigQuery supports any kind of filtering/querying for tables export at the moment:
https://cloud.google.com/bigquery/docs/exporting-data
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.extract
answered Nov 9 at 15:27
Igor Dvorzhak
624413
add a comment |
up vote
1
down vote
accepted
Doesn't look like BigQuery supports any kind of filtering/querying for tables export at the moment:
https://cloud.google.com/bigquery/docs/exporting-data
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.extract
answered Nov 9 at 15:27
Igor Dvorzhak
624413
add a comment |
up vote
1
down vote
accepted
up vote
1
down vote
accepted
Doesn't look like BigQuery supports any kind of filtering/querying for tables export at the moment:
https://cloud.google.com/bigquery/docs/exporting-data
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.extract
answered Nov 9 at 15:27
Igor Dvorzhak
624413
Doesn't look like BigQuery supports any kind of filtering/querying for tables export at the moment:
https://cloud.google.com/bigquery/docs/exporting-data
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.extract
answered Nov 9 at 15:27
Igor Dvorzhak
624413
answered Nov 9 at 15:27
Igor Dvorzhak
624413
answered Nov 9 at 15:27
Igor Dvorzhak
624413
answered Nov 9 at 15:27
Igor Dvorzhak
624413
624413
add a comment |
add a comment |
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An alternative is to create a temp table then read it with Spark.
– Dagang
Nov 23 at 21:05