pr feedback

docs/user-guide/arrays.rst

@@ -581,8 +581,8 @@ With Zarr format 3, a new sharding feature has been added to address this issue.
 With sharding, multiple chunks can be stored in a single storage object (e.g. a file).
 Within a shard, chunks are compressed and serialized separately.
 This allows individual chunks to be read independently.
-However, when writing data, a full shard must be written in one go for optimal performance and to
-avoid concurrency issues.
+However, when writing data, a full shard must be written in one go for optimal
+performance and to avoid concurrency issues.
 That means that shards are the units of writing and chunks are the units of reading.
 Users need to configure the chunk and shard shapes accordingly.
 
@@ -608,6 +608,7 @@ Sharded arrays can be created by providing the ``shards`` parameter to :func:`za
 
 In this example a shard shape of (1000, 1000) and a chunk shape of (100, 100) is used.
 This means that 10*10 chunks are stored in each shard, and there are 10*10 shards in total.
+Without the ``shards`` argument, there would be 10,000 chunks stored as individual files.
 
 Missing features in 3.0
 -----------------------

docs/user-guide/performance.rst

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