This video explains a very frequently used Batch Data Processing Pipeline & the Best Practices to improve the efficiency.

Best practices to follow during implementation:
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✅Proper File formats
✅Proper Partitioning
✅Transient EMR clusters instead of Persistent Cluster
✅External Hive Metastore instead of Embedded Metastore
✅Metadata Driven Ingestion Framework

Architecture:
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[ Ссылка ]

Reference Links:
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Transient Cluster on AWS from Scratch using boto3 | Trigger Spark job from AWS Lambda
[ Ссылка ]
Using the AWS Glue Data Catalog as the metastore for Hive
[ Ссылка ]
AWS Glue Data Catalog as the centralized metastore for Athena & PySpark from EMR
[ Ссылка ]
Generic Framework to load the data from s3 External Stage to Snowflake External Table
[ Ссылка ]

Check this playlist for more Data Engineering related videos:
[ Ссылка ]

Apache Kafka form scratch
[ Ссылка ]

Snowflake Complete Course from scratch with End-to-End Project with in-depth explanation--
[ Ссылка ]

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