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13 Spark Streaming Handling Errors and Exceptions | Handle Exception for data re-processing in Spark
Spark Streaming with PySpark | Structured Streaming Tutorial 2024
Video covers - How to handle error in Spark Streaming? How to handle Exception in Spark Streaming Application? How to store error data for re-processing in Spark Streaming? How to write data to JDBC Postgres table? Chapters: 00:00 - Introduction 00:41 - Error vs Exception in Spark Streaming 04:17 - Handling Error/Malformed data in Spark Streaming 10:02 - Handling Exception in Spark Streaming URLs: Github Code - https://github.com/subhamkharwal/spark-streaming-with-pyspark/blob/master/06_handling_errors_and_exceptions.ipynb Device data samples - https://github.com/subhamkharwal/spark-streaming-with-pyspark/blob/master/datasets/devices/device_data_samples.txt To setup Kafka with Spark in Local environment - https://youtu.be/BeZRe0f23hI JSON data Flattening and reading from files - https://youtu.be/wp_2CXyXV0w Keywords: Apache Spark, PySpark, Spark Streaming, Real-time Data Processing, Data Streaming, Big Data Analytics, PySpark Tutorial, Apache Spark Tutorial, Streaming Analytics, Spark Structured Streaming, PySpark Streaming, Big Data Processing. New video in every 3 days ā¤ļø Make sure to like and Subscribe.
About the course
Keywords: Spark Streaming with PySpark, Real time streaming, Structured Streaming Dive into the world of real-time data processing with our comprehensive playlist on Spark Streaming using PySpark! š Search Keywords: Apache Spark, PySpark, Spark Streaming, Real-time Data Processing, Data Streaming, Big Data Analytics, PySpark Tutorial, Apache Spark Tutorial, Streaming Analytics, Spark Structured Streaming, PySpark Streaming, Big Data Processing. š Playlist Overview: Unlock the power of Spark Streaming with PySpark through this in-depth playlist designed for beginners and intermediate users alike. Whether you're a data scientist, developer, or aspiring big data enthusiast, this series will guide you through the essentials of real-time data processing.
17lessons
2hours
Lessons
- 01 Spark Streaming with PySpark - Agenda
- 02 How Spark Streaming Works
- 03 Spark Streaming Local Environment Setup - Docker, Jupyter, PySpark and Kafka
- 04 Spark Streaming Read from Sockets | Convert Batch Code to Streaming Code
- 05 Spark Streaming Output Modes, Optimization and Background
- 06 Lambda and Kappa Architectures | Data Processing Architectures in Big Data
- 07 Spark Streaming Read from Files | Flatten JSON data
- 08 Spark Streaming Checkpoint Directory | Contents of Checkpoint Directory
- 09 Apache Kafka Basics & Architecture | Kafka Tutorial | Pub Sub Architecture | Learn Kafka in 15min
- 10 Spark Streaming Read from Kafka | Real time streaming from Kafka
- 11 Spark Streaming Triggers - Once, Processing Time & Continuous | Tune Kafka Streaming Performance
- 12 Spark Streaming Writing data to Multiple Sinks | foreachBatch | Writing data to JDBC(Postgres)
- 13 Spark Streaming Handling Errors and Exceptions | Handle Exception for data re-processing in Spark
- 14 Spark Streaming Event vs Processing Time | Late Arrival of Data | Stateful Processing |Watermarks
- 15 Tumbling, Sliding and Session Window Operations in Spark Streaming | Grouped Window Aggregations
- 16 Late Data Processing | Watermarks | Tumbling and Sliding Window Operations in Spark Streaming
- 17 Read and Write from Azure Cosmos DB using Spark | E2E Cosmos DB setup | NoSQL vs SQL Databases