Spark Streaming with Scala

11h 17m 52s
English
Paid
November 21, 2023

Stream big data in real time with Spark and integrate any data source, from Kafka to Twitter.

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Nothing static, all in motion.

Your probably know by now: Spark is the most popular computing engine for big data, the most maintained, and with a proven track record of performance. It's 100 times faster than the old MapReduce paradigm, and can easily be extended with machine learning and streaming capabilities, and much more.

In this course, we'll take the natural step forward: process big data as it arrives.

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# Title Duration
1 Welcome 18:05
2 Scala Recap 25:06
3 Spark Recap 27:11
4 Spark Streaming First Principles 08:29
5 Streaming DataFrames 27:17
6 Streaming Aggregations 15:58
7 Streaming Joins 25:24
8 Streaming Datasets 26:46
9 Discretized Streams (DStreams) 31:57
10 DStreams Transformations 28:40
11 DStreams Window Functions 32:11
12 Kafka & Structured Streaming 25:08
13 Kafka & DStreams 29:57
14 JDBC with Postgres 11:51
15 Akka and Akka Streams 28:58
16 Cassandra 21:55
17 Setting up a Twitter App 08:17
18 Our First Custom Receiver 15:45
19 Reading Tweets 20:05
20 Reading Tweets: Exercises 15:22
21 Sentiment Analysis on Tweets using NLP 20:50
22 Event Time Windows 31:20
23 Event Time Windows: Exercises 14:54
24 Processing Time Windows 11:16
25 Watermarks 25:16
26 Watermarks, Part 2 25:22
27 Arbitrary Stateful Computation 25:40
28 Arbitrary Stateful Computation 16:36
29 Setting up the REST Server and the Kafka Broker 27:51
30 Integrating Spark Structured Streaming, Test, Run! 33:54
31 You Rock! 00:31

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