Dataproc Operations
Google Cloud 2018
| Intermediate
- 10 Videos | 52m 1s
- Includes Assessment
- Earns a Badge
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
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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
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1.Spark and Hadoop Processes3m 5sUP NEXT
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2.Benefits of Cloud Dataproc2m 34s
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3.Job Monitoring and Logging3m 59s
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4.SSH into Master and Worker Nodes6m 36s
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5.Spark REPL3m 20s
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6.Separation of Compute and Storage4m 6s
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7.BigQuery Features and Capabilities3m 53s
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8.MapReduce with Big Data6m 11s
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9.Job Submission with Cloud Shell7m 39s
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10.Exercise: Dataproc and Cloud Shell Implementations10m 38s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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