Dataproc Operations

Google Cloud 2018    |    Intermediate
  • 10 videos | 52m 1s
  • Includes Assessment
  • Earns a Badge
Likes 46 Likes 46
Executing Dataproc implementations with big data can provide a variety of methods. Examine Dataproc implementations with Spark and Hadoop using the cloud shell and introduce BigQuery PySpark REPL package.

WHAT YOU WILL LEARN

  • describe the various Spark and Hadoop processes that can be performed with Dataproc
    recognize the benefits of separating storage and compute services using Cloud Dataproc
    recall the process of monitoring and logging Dataproc jobs
    demonstrate the process of using an SSH tunnel to connect to the master and worker nodes in a cluster
    define the Spark REPL package and how it's used in Linux
  • describe the compute and storage processes and the benefits of their separation and the virtualized distribution of Hadoop
    define BigQuery and its benefits for large-scale analytics
    describe the MapReduce programming model
    demonstrate the process of submitting multiple jobs with Dataproc
    recognize the various Dataproc and Cloud Shell job operations and implementations

IN THIS COURSE

  • Playable
    1. 
    Spark and Hadoop Processes
    3m 5s
    UP NEXT
  • Playable
    2. 
    Benefits of Cloud Dataproc
    2m 34s
  • Locked
    3. 
    Job Monitoring and Logging
    3m 59s
    FREE ACCESS
  • Locked
    4. 
    SSH into Master and Worker Nodes
    6m 36s
    FREE ACCESS
  • Locked
    5. 
    Spark REPL
    3m 20s
    FREE ACCESS
  • Locked
    6. 
    Separation of Compute and Storage
    4m 6s
    FREE ACCESS
  • Locked
    7. 
    BigQuery Features and Capabilities
    3m 53s
    FREE ACCESS
  • Locked
    8. 
    MapReduce with Big Data
    6m 11s
    FREE ACCESS
  • Locked
    9. 
    Job Submission with Cloud Shell
    7m 39s
    FREE ACCESS
  • Locked
    10. 
    Exercise: Dataproc and Cloud Shell Implementations
    10m 38s
    FREE ACCESS

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