XiangpengHao commented on code in PR #60:
URL: https://github.com/apache/datafusion-site/pull/60#discussion_r2003499924
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content/blog/2025-03-18-parquet-pruning.md:
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+---
+layout: post
+title: Parquet pruning in DataFusion: Read Only What Matters
+date: 2025-03-18
+author: Xiangpeng Hao
+categories: [performance]
+---
+
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+
+
+_Editor's Note: This blog was first published on [Xiangpeng Hao's blog].
Thanks to [InfluxData] for sponsoring this work as part of his PhD funding._
+
+[Xiangpeng Hao's blog]: https://blog.xiangpeng.systems/posts/parquet-to-arrow/
+[InfluxData]: https://www.influxdata.com/
+<hr/>
+
+Parquet has become the industry standard for storing columnar data, and
reading Parquet efficiently is crucial for query performance.
+
+To optimize this, DataFusion implements advanced Parquet support for effective
data pruning and decoding.
+
+However, achieving high performance adds complexity, and this is no exception.
This post provides an overview of the techniques used in DataFusion to
selectively read Parquet files.
+
+### The pipeline
+The diagram below illustrates the Parquet reading pipeline in DataFusion,
highlighting how data flows through various pruning stages before being
converted to Arrow format:
+
+<img src="/blog/images/parquet-pruning/read-parquet.jpg" alt="Parquet pruning
pipeline in DataFusion" width="100%" class="img-responsive">
+
+
+#### Background: Parquet file structure
+As shown in the figure above, each Parquet file has multiple row groups. Each
row group contains a set of columns, and each column contains a set of pages.
+
+Pages are the smallest units of data in Parquet files and typically contain
compressed and encoded values for a specific column. This hierarchical
structure enables efficient columnar access and forms the foundation for the
pruning techniques we'll discuss.
+
+Check out [Querying Parquet with Millisecond
Latency](https://www.influxdata.com/blog/querying-parquet-millisecond-latency/)
for more details on the Parquet file structure.
+
+#### 1. Read metadata
+DataFusion first reads the Parquet metadata to understand the data in the
file.
+Metadata often includes data schema, the exact location of each row group and
column chunk, and their corresponding statistics (e.g., min/max values).
+It also optionally includes [page-level
stats](https://parquet.apache.org/docs/file-format/pageindex/) and [Bloom
filters](https://www.influxdata.com/blog/using-parquets-bloom-filters/).
+This information is used to prune the file before reading the actual data.
+
+[Fetching
metadata](https://github.com/apache/datafusion/blob/31701b8dc9c6486856c06a29a32107d9f4549cec/datafusion/core/src/datasource/physical_plan/parquet/reader.rs#L118)
requires up to two network requests: one to read the footer size from the end
of the file, and another to read the footer itself.
Review Comment:
Yes, I hoped someone could do a study of "Parquet in the wild", which
analyzes how people use Parquet: what features they use, how large are the
metadata sizes etc.
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