Streaming Data Architectures: Processing Streaming Data with Spark

Data Science    |    Intermediate
  • 11 videos | 52m 10s
  • Includes Assessment
  • Earns a Badge
Likes 43 Likes 43
Process streaming data with Spark, the analytic engine built on Hadoop. In this course, you will discover how to develop applications in Spark to work with streaming data and generate output. Topics include the following: Configure a streaming data source; Use Netcat and write applications to process the data stream; Learn the effects of using the Update mode on your stream processing application's output; Write a monitoring application that listens for new files added to a directory; Compare the append output with the update mode; Develop applications to limit files processed in each trigger; Use Spark's Complete mode for output; Perform aggregation operations on streaming data with the DataFrame API; Process streaming data with Spark SQL queries.

WHAT YOU WILL LEARN

  • install the latest available version of PySpark
    configure a streaming data source using Netcat and write an application to process the stream
    describe the effects of using the Update mode for the output of your stream processing application
    write an application to listen for new files being added to a directory and process them as soon as they come in
    compare the Append output to the Update mode and distinguish between the two
  • develop applications that limit the files processed in each trigger and use Spark's Complete mode for the output
    perform aggregation operations on streaming data using the DataFrame API
    work with Spark SQL in order to process streaming data using SQL queries
    define and apply standard, re-usable transformations for streaming data
    recall they key ways to use Spark for streaming data and explore the ways to process streams and generate output

IN THIS COURSE

  • 2m 10s
  • 2m 39s
    Learn how to install the latest version of PySpark. FREE ACCESS
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    3.  Setting Up a Socket Stream with Netcat
    8m 53s
    In this video, you will configure a streaming data source using Netcat and write an application to process the stream. FREE ACCESS
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    4.  The Update Output Mode
    3m 32s
    Upon completion of this video, you will be able to describe the effects of using the Update mode for the output of your stream processing application. FREE ACCESS
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    5.  Using a File Input Stream
    7m 50s
    In this video, you will learn how to write an application to listen for new files being added to a directory and process them as soon as they are added. FREE ACCESS
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    6.  The Append Output Mode
    2m 15s
    Learn how to compare the output of Append to the output of Update mode, and distinguish between the two. FREE ACCESS
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    7.  The Complete Output Mode
    6m 35s
    Find out how to develop applications that limit the files processed in each trigger and use Spark's Complete mode for the output. FREE ACCESS
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    8.  Aggregations on Streaming Data
    4m 6s
    In this video, you will learn how to perform aggregation operations on streaming data using the DataFrame API. FREE ACCESS
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    9.  SQL Operations on Streaming Data
    4m 59s
    Find out how to work with Spark SQL in order to process streaming data using SQL queries. FREE ACCESS
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    10.  User-Defined Functions (UDFs)
    4m 41s
    Learn how to define and apply standard, reusable transformations for streaming data. FREE ACCESS
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    11.  Exercise: Processing Streaming Data
    4m 30s
    After completing this video, you will be able to recall the key ways to use Spark for streaming data and explore the ways to process streams and generate output. FREE ACCESS

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