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Big Data For Architects
Overview
Course Structure and Approach (1:58)
Course Pre-requisites (2:09)
Course Audience (1:50)
About me (2:34)
Environment Setup
Google Cloud Account Setup (1:39)
Creating a Dataproc Cluster (12:47)
GCP Account Best Practices (2:55)
Data Files
Holistic View, Architectures and Pipelines
Big Data Logical Architecture (20:00)
Evolution of Big Data Technologies (11:15)
Key Big Data Architectures (12:57)
Typical Big Data Batch Pipeline (2:13)
Typical Big Data Streaming Pipelines (8:31)
Bonus 1: Another Example of Big Data Streaming Pipeline (2:41)
Bonus 2: Another Example of Big Data Streaming Pipeline (3:09)
Key Ingestion/DataFlow Frameworks
Factors to consider while comparing Ingestion frameworks (12:18)
Kafka vs Flume (10:54)
NiFi vs Kafka (12:58)
Sqoop vs Flume (6:11)
Sqoop vs Kafka Connect (6:33)
Hands-on NiFi Installation (7:11)
Hands-on Kafka Installation (7:39)
Hands-on Kafka and NiFi Integration Background (1:41)
Hands-on Kafka and NiFi Integration (24:10)
Key Storage Frameworks
Factors to consider while comparing Storage frameworks (9:16)
HDFS vs HBase (6:18)
HBase vs Kudu (5:25)
HDFS vs Kudu (4:03)
HBase vs Cassandra (7:27)
Data formats
Text vs Binary (3:29)
Interoperability (2:11)
Row oriented vs Column oriented (6:43)
Splittable Formats (5:15)
Schema Evolution (9:34)
Comparing Data Formats (8:28)
Hands-on Sqoop Installation on DataProc (11:49)
Hands-on Big Data Batch Pipeline Use Avro format (17:47)
Key Data Processing Frameworks
Factors to consider while comparing Processing frameworks (13:16)
MR vs Spark Logical Architecture Perspective (7:17)
MR vs Spark Performance Perspective (1:29)
Spark vs Tez (4:23)
Spark vs Flink (10:47)
Kafka Streams vs Spark Streaming (10:31)
Spark 2.x Streaming vs Spark 1.x Streaming (5:39)
Spark Core vs Spark SQL (4:21)
Hands-on Kafka & Spark Streaming Integration (12:01)
Key Data Analysis Frameworks
Factors to consider while comparing Analysis frameworks (10:23)
Hive vs Impala (7:09)
Hive vs Pig (5:49)
Hive vs Spark SQL (4:42)
Hive vs Hive LLAP vs Impala (6:49)
Hive vs KSQL (6:21)
KSQL vs KSQLDB (Confluent has renamed KSQL to KSQLDB) (4:47)
Hands-on KSQL (5:55)
Hands-on Write to a Stream and Table Using KSQL (12:24)
Hands-on Streaming ETL Pipeline Background (6:09)
Hands-on Build a Scalable ETL Pipeline with Kafka Connect - part 1 (17:31)
Hands-on Build a Scalable ETL Pipeline with Kafka Connect - part 2 (3:53)
Delta Lake
Delta Architecture (6:17)
Why Delta Lake (5:12)
Challenges with Data Lake (3:07)
Delta Lake Demo (24:40)
Bonus
Solr vs ElasticSearch (7:00)
Cloudera Search vs Solr (2:47)
KSQL vs KStreams (6:55)
Epilogue
Conclusion (1:10)
HBase vs Kudu
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