Big Data for Architects [Video]
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Free ChapterIntroduction
-
Setting Up the Environment
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Holistic View of Architectures and Pipelines
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Key Ingestion/Dataflow Frameworks
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Key Storage Frameworks
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Data formats
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Key Data Processing Frameworks
- Factors to Consider while Comparing Processing Frameworks
- MapReduce (MR) Versus Spark Logical Architecture
- MapReduce (MR) Versus Spark Performance
- Spark Versus Tez
- Spark Versus Flink
- Kafka Streams Versus Spark Streaming
- Spark 2.x Streaming Versus Spark 1.x Streaming
- Spark Core Versus Spark Structured Query Language (SQL)
- Integrating Kafka and Spark Streaming
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Key Data Analysis Frameworks
- Factors to Consider while Comparing Analysis Frameworks
- Hive Versus Impala
- Hive Versus Pig
- Hive Versus Spark Structured Query Language (SQL)
- Hive Versus Hive Live Long and Process (LLAP) Versus Impala
- Hive Versus KSQL
- KSQL Versus KSQLDB
- Hands-On KSQL
- Writing to a Stream and Table Using KSQL
- Streaming Extract, Transform, Load (ETL) Pipeline Background
- Building a Scalable Extract, Transform, Load (ETL) Pipeline with Kafka Connect - Part 1
- Building a Scalable Extract, Transform, Load (ETL) Pipeline with Kafka Connect - Part 2
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Delta Lake
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Additional Material
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Summary
About this
video
Do you want a guide that will help you to pick the right Big Data technology for your project? Or do you want to get a solid understanding of the Big Data architecture and pipelines? This course will help you out.
After highlighting the course structure and learning objectives, the course will take you through the steps needed for setting up the environment. Next, you will understand the Big Data logical architecture, study the evolution of Big Data technologies, and explore Big Data pipelines. Moving along, you will become familiar with ingestion frameworks, such as Kafka, Flume, Nifi, and Sqoop. Next, you will learn about key storage frameworks, such as HDFS, HBase, Kudu, and Cassandra. Finally, you will go through the various data formats and uncover key data processing and data analysis frameworks.
By the end of this course, you will have a good understanding of the Big Data architecture and technologies and will have developed the skills to build real-world Big Data pipelines.
All the resources and support files for this course are available at https://github.com/PacktPublishing/Big-Data-for-Architects
- Publication date:
- January 2021
- Publisher
- Packt
- Duration
- 8 hours 19 minutes
- ISBN
- 9781801075596