spark-bigquery's Introduction

MAINTENANCE MODE

THIS PROJECT IS IN MAINTENANCE MODE DUE TO THE FACT THAT IT'S NOT WIDELY USED WITHIN SPOTIFY. WE'LL PROVIDE BEST EFFORT SUPPORT FOR ISSUES AND PULL REQUESTS BUT DO EXPECT DELAY IN RESPONSES.

spark-bigquery

Google BigQuery support for Spark, SQL, and DataFrames.

spark-bigquery version	Spark version	Comment
0.2.x	2.x.y	Active development
0.1.x	1.x.y	Development halted

To use the package in a Google Cloud Dataproc cluster:

spark-shell --packages com.spotify:spark-bigquery_2.10:0.2.0

To use it in a local SBT console:

import com.spotify.spark.bigquery._

// Set up GCP credentials
sqlContext.setGcpJsonKeyFile("<JSON_KEY_FILE>")

// Set up BigQuery project and bucket
sqlContext.setBigQueryProjectId("<BILLING_PROJECT>")
sqlContext.setBigQueryGcsBucket("<GCS_BUCKET>")

// Set up BigQuery dataset location, default is US
sqlContext.setBigQueryDatasetLocation("<DATASET_LOCATION>")

Usage:

// Load everything from a table
val table = sqlContext.bigQueryTable("bigquery-public-data:samples.shakespeare")

// Load results from a SQL query
// Only legacy SQL dialect is supported for now
val df = sqlContext.bigQuerySelect(
  "SELECT word, word_count FROM [bigquery-public-data:samples.shakespeare]")

// Save data to a table
df.saveAsBigQueryTable("my-project:my_dataset.my_table")

If you'd like to write nested records to BigQuery, be sure to specify an Avro Namespace. BigQuery is unable to load Avro Namespaces with a leading dot (.nestedColumn) on nested records.

// BigQuery is able to load fields with namespace 'myNamespace.nestedColumn'
df.saveAsBigQueryTable("my-project:my_dataset.my_table", tmpWriteOptions = Map("recordNamespace" -> "myNamespace"))