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[FAQ Bot] NEW: Why does Spark write multiple parquet files after repartitioning a DataF #238

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[FAQ Bot] NEW: Why does Spark write multiple parquet files after repartitioning a DataF #238

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13 changes: 13 additions & 0 deletions ...-zoomcamp/module-6/060_a71d2105aa_spark-write-multiple-parquet-per-partition.md
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---
id: a71d2105aa
question: Why does Spark write multiple parquet files after repartitioning a DataFrame?
sort_order: 60
---

Spark processes data in partitions. When you write a DataFrame to disk, Spark writes each partition as a separate output file. For example:

```python
trips.repartition(4).write.parquet("output/")
```

This creates four parquet files because the DataFrame now has four partitions. This behavior enables Spark to write data in parallel and can improve performance on large datasets.