Advanced Spark Topics

Advanced Spark related topics and tutorials. These articles are focusing on more advanced Spark topics incl. framework, architecture, etc. 

Advanced Spark Topics
Schema Merging (Evolution) with Parquet in Spark and Hive

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access_time 8 months ago

Schema evolution is supported by many frameworks or data serialization systems such as Avro, Orc, Protocol Buffer and Parquet. With schema evolution, one set of data can be stored in multiple files with different but compatible schema. In Spark, Parquet data source can detect and merge sch...

Improve PySpark Performance using Pandas UDF with Apache Arrow

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access_time 9 months ago

Apache Arrow is an in-memory columnar data format that can be used in Spark to efficiently transfer data between JVM and Python processes. This currently is most beneficial to Python users that work with Pandas/NumPy data. In this article, ...

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access_time 2 years ago

Scenario Recently I created an Oozie workflow which contains one Spark action. The Spark action master is yarn and deploy mode is cluster. Each time when the job runs about 30 minutes, the application fails with errors like the following: Application applicatio...

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access_time 2 years ago

In my previous post about Data Partitioning in Spark (PySpark) In-depth Walkthrough , I mentioned how to repartition data frames in Spark using repartition ...

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access_time 2 years ago

Data partitioning is critical to data processing performance especially for large volume of data processing in Spark. Partitions in Spark won’t span across nodes though one node can contains more than one partitions. When processing, Spark assigns one task for each partition and each worker threa...

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access_time 2 years ago

Overview For SQL developers that are familiar with SCD and merge statements, you may wonder how to implement the same in big data platforms, considering database or storages in Hadoop are not designed/optimised for record level updates and inserts. In this post, I’m going to demons...

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