Following on from the previous   experiments with Postgres & pgbench. A quick look at how the workload is seen from the Nutanix CVM.
The Linux VM running postgres has two virtual disks:
One is taking transaction log writes.
The other is doing reads and writes from the main datafiles.
Since the database size is small (50% the size of the Linux RAM) – the data is mostly cached inside the guest, and so most reads do not hit storage. As a result we only see writes going to the DB files.
Additionally, we see that database datafile writes the arrive in a bursty fashion, and that these write bursts are more intense (~10x) than the log file writes.
Despite the database flushes ocurring in bursts with a decent amount of concurrency the Nutanix CVM provides an average of 1.5ms write response time.
From the Nutanix CVM port 2009 handler, we can access the individual vdisk statistics. In this particular case vDisk 45269 is the data file disk, and 40043 is the database transaction log disk.
The vdisk categorizer correctly identifies the database datafile write pattern as highly random.
As a result, the writes are passed into the replicated oplog
Meanwhile the log writes are categorized as mostly sequential, which is expected for a database log file workload.
Even though the log writes are sequential, they are low-concurrency and small size (looks like mostly 16K-32K). This write pattern is also a good candidate for oplog.
What space savings should you expect when running databases with default compression in a Nutanix cluster? When we ran the TPCx-HCI benchmark on our cluster we realized about 2:1 savings from compression alone. The TPCx-HCI benchmark mimics a database consolidation setup, meaning that there are many databases per host. The uncompressed data size was about 45TB.
Additionally, we configured data at rest encryption (DARE). Using the cluster features allows us to both compress and encrypt (compression first, then encrypt). If the database engine itself handled encryption, it would reduce the ability to compress.
Like ZFS, the Nutanix filesystem uses LZ4 compressiom and 2:1 is about in-line with expectations for a realistic dataset. The TPCx-HCI benchmark uses the E-Gen data generation tool to populate the databases. E-Gen was developed for the TPC-E benchmark and uses sources such as census data and NYSE stock listings to generate real data rather than machine generated strings.