GCP Dataproc spark consuming BigQuery

Question

I'm very new on GCP Google Cloud Platform, so I hope my question will not look so silly.

Footstage:

The main goals is gather few extend tables from BigQuery and apply few transformations. Because of the size of the tables I'm planning use Dataproc deploying a Pyspark script, ideally I would be able to use sqlContext to apply few sql queries to the DFs (tables pulled from BQ). Finally, I could easily dump this info into a file within a data storage bucket.

Questions :

• Can I use import google.datalab.bigquery as bq within my Pyspark script?

• Is this proposed schema the most efficient or instead I might validate any other? keep in mind that I need to create many temporal queries and this is why I though on Spark.

• I expect to use pandas and bq to read the results queries as pandas df following this example. Later, I might use sc.parallelize from Spark to transform the pandas df into a spark df. Is this approach the right one?

my script

• Update:

After have a back and forth with @Tanvee that kindly attend this question we conclude that GCP requires an intermediate allocation step when you need to read data from DataStorage into your Dataproc. Briefly, your spark or hadoop script might need a temporal bucket where store the data from the table and then bring it into Spark.

References:

Big Query Connector \ Deployment

thanks so much

Answer 1

You can directly use following options to connect bigquery table from spark.

1. You can also use spark-bigquery connectors https://github.com/samelamin/spark-bigquery to directly run your queries on dataproc using spark.

2. https://github.com/GoogleCloudPlatform/spark-bigquery-connector This is new connector which is in beta. This is spark datasource api to bigquery which is easy to use.

Please refer following link: Dataproc + BigQuery examples - any available?

Answer 2

You will need to use BigQuery connector for spark. There are some examples in the GCP documentation here and here. It will create RDD which you can convert to dataframe and then you will be able to perform all typical transformations. Hope that helps.