by | Released August 2015 | ISBN: 9781491934951

As it becomes easier to create data, we are now faced with the need to collect and analyze at scales never seen before. In this practical video course, Apache Cassandra evangelist Patrick McFadin shows how to solve time-series data problems with technologies from Team Apache: Kafka, Spark and Cassandra. To learn how to work with these technologies, you'll work with an example weather collection network and the challenges it can produce.Through the course of this video, you'll investigate:Kafka: get your data under control by handling real-time data feeds with this message brokerSpark: learn how this parallel processing framework can quickly and efficiently analyze massive amounts of dataSpark Streaming: perform effective stream analysis by ingesting data in micro-batchesCassandra: understand how this distributed database works by examining use cases where scaling and uptime are criticalCassandra Query Language (CQL): use this language to navigate your data models, from creating tables to inserting and selecting dataSpark and Cassandra: combine these powerful tools to perform expressive analytics over large volumes of dataPatrick McFadin is one of the leading experts of Apache Cassandra and data modeling techniques. As the Chief Evangelist for Apache Cassandra and consultant for DataStax, he has helped build some of the largest and exciting deployments in production. Prior to DataStax, he was Chief Architect at Hobsons, an education services company. Show and hide more Publisher resources Download Example Code

1. Introduction
   • Introduction to Time Series Problems 00:09:58
2. Kafka
   • Kafka Architecture and Deployment 00:11:33
   • Kafka Usage 00:03:42
3. Spark
   • Introduction to Spark 00:15:43
   • Spark Architecture 00:12:02
4. Spark Streaming
   • Spark Streaming: Windows & Slides 00:08:35
   • Spark Streaming: Ingestion Sources & Using Kafka 00:08:32
   • Sparks Streaming: Operations on the Stream 00:01:30
5. Cassandra
   • Introduction to Cassandra 00:08:56
   • Cassandra Basic Architecture 00:11:59
   • Replication, High Availability and Multi Datacenter 00:14:06
   • Cassandra Weather Website Example 00:11:46
   • Cassandra Query Language (CQL) 00:18:00
   • Cassandra Partitions & Clustering 00:08:22
   • Cassandra Read and Write Path 00:12:17
   • Working with Cassandra 00:06:32
   • Cassandra Drivers and Access Patterns 00:10:37
6. Spark and Cassandra
   • Spark and Cassandra Architecture 00:12:00
   • Analyzing Cassandra Data & Spark SQL 00:12:12
   • Spark and Cassandra DataStax Enterprise 00:04:31
7. Real World Use Cases
   • Real World Use Cases: Streaming Problems 00:17:11
   • Real World Use Cases: In-place Analytic Problems 00:10:58
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