Spark Streaming with Scala

11h 17m 52s
English
Paid

Course description

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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#1: Welcome

All Course Lessons (31)

#Lesson TitleDurationAccess
1
Welcome Demo
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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