with Henry Quach, Alan Barnes
Data scientists, engineers, or anyone who is interested in learning about Spark.
Time to complete:
Apache Spark is an open source processing engine built around speed, ease of use, and analytics. If you have large amounts of data that requires low latency processing that a typical Map Reduce program cannot provide, Spark is the alternative. Spark performs at speeds up to 100 times faster than Map Reduce for iterative algorithms or interactive data mining. Spark provides in-memory cluster computing for lightning fast speed and supports Java, Scala, and Python APIs for ease of development.
Spark combines SQL, streaming and complex analytics together seamlessly in the same application to handle a wide range of data processing scenarios. Spark runs on top of Hadoop, Mesos, standalone, or in the cloud. It can access diverse data sources such as HDFS, Cassandra, HBase, or S3.
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After completing this course, you should be able to:
Before taking this course, you should have the following background:
The minimum passing mark for the course is 60%, where the final test is worth 100% of the course mark. You have 3 attempts to take the test