Big Data analysis is an essential component of any company organization that works with mass amounts of data, and it’s a constantly adapting and innovating field. Spark Streaming is a new and quickly developing technology for processing mass data sets in real time. Whether it’s clickstream data from a major website, sensor data from an Internet of Things deployment, financial data, or any other large stream of data, Spark Streaming has the capability to transform and analyze that data as it is created. The professional applications of this technology are obvious, and this course will get you up to speed not just in Spark Streaming, but in Big Data generally, so you can confidently start looking for high-paying Big Data jobs.
- Access 34 lectures & 5.5 hours of content 24/7
- Get a crash course in the Scala programming language
- Learn how Apache Spark operates on a cluster
- Set up discretized streams w/ Spark Streaming & transform them as data is received
- Analyze streaming data over sliding windows of time
- Maintain stateful information across streams of data
- Connect Spark Streaming w/ highly scalable source of data, including Kafka, Flume, & Kinesis
- Dump streams of data in real-time to NoSQL databases such as Cassandra
- Run SQL queries on streamed data in real time
- Train machine learning models in real time w/ streaming data, & use them to make predictions
- Package, deploy & run self-contained Spark Streaming code to a real Hadoop cluster using Amazon Elastic MapReduce
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