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docs/user-guide/arrays.rst

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@@ -581,8 +581,8 @@ With Zarr format 3, a new sharding feature has been added to address this issue.
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With sharding, multiple chunks can be stored in a single storage object (e.g. a file).
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Within a shard, chunks are compressed and serialized separately.
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This allows individual chunks to be read independently.
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However, when writing data, a full shard must be written in one go for optimal performance and to
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avoid concurrency issues.
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However, when writing data, a full shard must be written in one go for optimal
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performance and to avoid concurrency issues.
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That means that shards are the units of writing and chunks are the units of reading.
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Users need to configure the chunk and shard shapes accordingly.
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In this example a shard shape of (1000, 1000) and a chunk shape of (100, 100) is used.
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This means that 10*10 chunks are stored in each shard, and there are 10*10 shards in total.
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Without the ``shards`` argument, there would be 10,000 chunks stored as individual files.
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Missing features in 3.0
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-----------------------

docs/user-guide/performance.rst

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@@ -69,7 +69,9 @@ Sharding
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If you have large arrays but need small chunks to efficiently access the data, you can
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use sharding. Sharding provides a mechanism to store multiple chunks in a single
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storage object or file. This can be useful because traditional file systems and object
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storage systems may have issues storing and accessing many files.
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storage systems may have performance issues storing and accessing many files.
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Additionally, small files can be inefficient to store if they are smaller than the
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block size of the file system.
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Picking a good combination of chunk shape and shard shape is important for performance.
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The chunk shape determines what unit of your data can be read independently, while the

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