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47 lines
1.7 KiB
ReStructuredText
47 lines
1.7 KiB
ReStructuredText
The Plasma Object Store
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=======================
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Plasma is a high-performance shared memory object store originally developed in
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Ray and now being developed in `Apache Arrow`_. See the `relevant
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documentation`_.
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Using Plasma with Huge Pages
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----------------------------
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On Linux, it is possible to increase the write throughput of the Plasma object
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store by using huge pages. You first need to create a file system and activate
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huge pages as follows.
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.. code-block:: shell
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sudo mkdir -p /mnt/hugepages
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gid=`id -g`
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uid=`id -u`
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sudo mount -t hugetlbfs -o uid=$uid -o gid=$gid none /mnt/hugepages
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sudo bash -c "echo $gid > /proc/sys/vm/hugetlb_shm_group"
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# This typically corresponds to 20000 2MB pages (about 40GB), but this
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# depends on the platform.
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sudo bash -c "echo 20000 > /proc/sys/vm/nr_hugepages"
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**Note:** Once you create the huge pages, they will take up memory which will
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never be freed unless you remove the huge pages. If you run into memory issues,
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that may be the issue.
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You need root access to create the file system, but not for running the object
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store.
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You can then start Ray with huge pages on a single machine as follows.
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.. code-block:: python
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ray.init(huge_pages=True, plasma_directory="/mnt/hugepages")
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In the cluster case, you can do it by passing ``--huge-pages`` and
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``--plasma-directory=/mnt/hugepages`` into ``ray start`` on any machines where
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huge pages should be enabled.
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See the relevant `Arrow documentation for huge pages`_.
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.. _`Apache Arrow`: https://arrow.apache.org/
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.. _`relevant documentation`: https://arrow.apache.org/docs/python/plasma.html#the-plasma-in-memory-object-store
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.. _`Arrow documentation for huge pages`: https://arrow.apache.org/docs/python/plasma.html#using-plasma-with-huge-pages
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