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Airflow and Google Dataproc
In Data Engineer's Lunch #76, Arpan Patel will cover how to
connect Airflow and Google Dataproc with a demo using an Airflow
DAG to create a Dataproc cluster, submit an Apache Spark job to
Dataproc, and destroy the Dataproc cluster upon completion.
Arpan Patel
Engineer @ Anant
Google Dataproc
● Fully managed and highly scalable service for running
Apache Spark, Apache Flink, Presto, and 30+ open source
tools and frameworks
○ Lets you take advantage of open source data tools
for batch processing, querying, streaming, and
machine learning
● Dataproc clusters are quick to start, scale, and shutdown,
with each of these operations taking 90 seconds or less,
on average
● Built-in integration with other Google Cloud Platform
services, such as BigQuery, Cloud Storage, Cloud
Bigtable, Cloud Logging, and Cloud Monitoring
● Can easily interact with clusters and Spark or Hadoop
jobs through the Google Cloud console, the Cloud SDK, or
the Dataproc REST API
Google Dataproc
● https://cloud.google.com/dataproc/docs/concepts
/versioning/dataproc-version-clusters
○ https://cloud.google.com/dataproc/docs/co
ncepts/versioning/dataproc-release-2.0
○ https://cloud.google.com/dataproc/docs/co
ncepts/versioning/dataproc-release-1.5
● Can run on GCE / GKE
● Dataproc Serverless for Spark
Google Dataproc + DataStax Astra
● Cluster Properties
○ dataproc:dataproc.conscrypt.provider.enable=false
● Job Properties
○ spark.jars.packages → com.datastax.spark:spark-cassandra-connector_2.12:3.1.0
● DAG param mappings to GCP REST API mappings
○ need to convert camel casing to "_". For example masterConfig -> master_config
○ if we want to use GKE for Dataproc cluster creation, then need to swap cluster_config for
virtual_cluster_config
Demo
● Open repo on Gitpod
● Set GCP Connection and Variables
● Run Dag that will:
○ Spin up Dataproc Cluster on GCE
○ Submit Dataproc Spark Job to read from DataStax Astra
○ Destroy Cluster
Strategy: Scalable Fast Data
Architecture: Cassandra, Spark, Kafka
Engineering: Node, Python, JVM,CLR
Operations: Cloud, Container
Rescue: Downtime!! I need help.
www.anant.us | solutions@anant.us | (855) 262-6826
3 Washington Circle, NW | Suite 301 | Washington, DC 20037

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Data Engineer's Lunch #76: Airflow and Google Dataproc

  • 1. Version 1.0 Airflow and Google Dataproc In Data Engineer's Lunch #76, Arpan Patel will cover how to connect Airflow and Google Dataproc with a demo using an Airflow DAG to create a Dataproc cluster, submit an Apache Spark job to Dataproc, and destroy the Dataproc cluster upon completion. Arpan Patel Engineer @ Anant
  • 2. Google Dataproc ● Fully managed and highly scalable service for running Apache Spark, Apache Flink, Presto, and 30+ open source tools and frameworks ○ Lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning ● Dataproc clusters are quick to start, scale, and shutdown, with each of these operations taking 90 seconds or less, on average ● Built-in integration with other Google Cloud Platform services, such as BigQuery, Cloud Storage, Cloud Bigtable, Cloud Logging, and Cloud Monitoring ● Can easily interact with clusters and Spark or Hadoop jobs through the Google Cloud console, the Cloud SDK, or the Dataproc REST API
  • 3. Google Dataproc ● https://cloud.google.com/dataproc/docs/concepts /versioning/dataproc-version-clusters ○ https://cloud.google.com/dataproc/docs/co ncepts/versioning/dataproc-release-2.0 ○ https://cloud.google.com/dataproc/docs/co ncepts/versioning/dataproc-release-1.5 ● Can run on GCE / GKE ● Dataproc Serverless for Spark
  • 4. Google Dataproc + DataStax Astra ● Cluster Properties ○ dataproc:dataproc.conscrypt.provider.enable=false ● Job Properties ○ spark.jars.packages → com.datastax.spark:spark-cassandra-connector_2.12:3.1.0 ● DAG param mappings to GCP REST API mappings ○ need to convert camel casing to "_". For example masterConfig -> master_config ○ if we want to use GKE for Dataproc cluster creation, then need to swap cluster_config for virtual_cluster_config
  • 5. Demo ● Open repo on Gitpod ● Set GCP Connection and Variables ● Run Dag that will: ○ Spin up Dataproc Cluster on GCE ○ Submit Dataproc Spark Job to read from DataStax Astra ○ Destroy Cluster
  • 6. Strategy: Scalable Fast Data Architecture: Cassandra, Spark, Kafka Engineering: Node, Python, JVM,CLR Operations: Cloud, Container Rescue: Downtime!! I need help. www.anant.us | solutions@anant.us | (855) 262-6826 3 Washington Circle, NW | Suite 301 | Washington, DC 20037