---
title: "Discussion on \"Partitioning in Spark: HashPartitioner, RangePartitioner, and Custom Strategies\" | Hashnode"
description: "Discussion on \"Partitioning in Spark: HashPartitioner, RangePartitioner, and Custom Strategies\". Partition count and strategy determine whether your Spark job scales linearly or falls apart at 10x data — here is what happens under the hood"
url: "https://hashnode.com/posts/spark-partitioning-hash-range-custom/69e437bef98b558fec73a322"
---

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# [Partitioning in Spark: HashPartitioner, RangePartitioner, and Custom Strategies](https://abstractalgorithms.hashnode.dev/spark-partitioning-hash-range-custom?utm_source=hashnode&utm_medium=feed)

Partition count and strategy determine whether your Spark job scales linearly or falls apart at 10x data — here is what happens under the hood

Apr 19 · 26 min read · abstractalgorithms.hashnode.dev  
Updated Jun 18  
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-   [#apache-spark](https://hashnode.com/tag/apache-spark)
-   [#partitioning](https://hashnode.com/tag/partitioning)
-   [#performance](https://hashnode.com/tag/performance)
-   [#intermediate](https://hashnode.com/tag/intermediate)

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