As mentioned in blog post 1 we have improved the capabilities to handle
very large write bandwidth and blog post 2 improved the checkpointing of
disk data columns in MySQL Cluster 8.0.20.
We wanted to verify that these changes were succesful. To do this we
selected to use the YCSB benchmark. This is a very simple benchmark,
it contains one table with in our variant 2 columns. The first
column is the primary key, the second key contains the payload data
and is stored in VARCHAR(29500) column that is stored on disk.
The first part of the benchmark fills the database. The database is
mostly stored in a tablespace that is setup in accordance with the
blog post 3. This means that we had a tablespace size of 20 TBytes.
We loaded 600M rows, thus creating a database size of 18 TByte.
The load phase inserted 44.500 rows per second. This means that we
loaded 1.25 GByte per second into the database. The bottleneck in
both the load phase and the benchmark run phase was mainly the
NVMe drives, but in some cases also the 25G Ethernet became the
bottleneck. The CPUs were never loaded more than 20%, thus never
becoming a bottleneck.
From this we can conclude that the setup and use of the NVMe drives
is the most important part of achieving extreme write rates for
use cases where NDB Cluster is used for file write loads.
The cluster setup used 2 data nodes, each of the data nodes was a bare
metal server in the Oracle Cloud (OCI) that had 8 NVMe drives (2 used
for logs and checkpoints and 6 used for the tablespace). The servers
had 52 CPU cores each. Instead of setting up a RAID on the 6 NVMe drives
we instead opted for one file system per NVMe drive and added one
data file per NVMe drive to NDB. This meant that NDB handled the
spread of writes on the different data files. Thus no complex RAID
solutions was required. However to get the best possible performance
it was necessary to use SSD overprovisioning.
The disk usage and CPU usage and network usage during this benchmark can
be found in blog post 4. The mean latency of those transactions was a bit more
than 2 milliseconds where reads took a bit more than 1 ms and writes around
The actual benchmark consisted of 50% reads and 50% writes. Here we
achieved almost 70.000 transactions per second. This meant that we
read 1 GByte per second in parallel with writing 1 GByte per second.
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