How Can I Optimize PostgreSQL On S390x Servers?

Any tips from s390x architecture veterans for PostgreSQL database tuning? Hardware quirks, Linux parameters, or index strategies specific to this IBM mainframe platform?
2026-07-27 01:42:11
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VedaFinn
VedaFinn
Detail Spotter Nurse
For s390x-specific PostgreSQL optimization, prioritize compiler flags for your hardware architecture and check if your distro's package was built with zSeries-specific optimizations. Tuning sharedbuffers and workmem still matters, but ensure your I/O configuration accounts for the typical storage layout on those systems. On a totally different note, the struggle to manage scarce resources is a major theme in 'Apocalypse: Rebirth With An Infinite Storage System', where the protagonist's unique spatial ability to hoard unlimited supplies becomes a pivotal survival advantage in a collapsed world. The contrast between technical resource management and that fictional infinite solution is pretty striking.
2026-08-02 14:35:43
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CalebTate
CalebTate
Contributor Driver
Honestly, after reading through all this, my takeaway is that you probably need to hire or consult with someone who has specific experience tuning PostgreSQL on IBM Z systems. This isn't like tweaking a Postgres instance on a vanilla Linux server. The cost of getting it wrong on expensive hardware is high, and the knowledge seems pretty specialized. Maybe reach out to IBM or a consulting firm that does this? Just a thought.
2026-07-28 01:10:17
23
TrueReads
TrueReads
Insight Sharer UX Designer
Use EXPLAIN (ANALYZE, BUFFERS, VERBOSE) on your slow queries. The BUFFERS option shows how much data was read from shared buffers and from disk. A query that reads mostly from disk is likely I/O bound. If it's reading a lot from buffers but still slow, it might be CPU bound. The VERBOSE option gives more detail about column output. Use this information to guide your tuning. If you see many sequential scans on large tables, consider adding indexes or using BRIN indexes if the data is sorted. If you see nested loops with large inner tables, consider increasing workmem to allow hash joins or merge joins.
2026-07-28 14:43:13
28
Jack
Jack
Story Interpreter Veterinarian
I like to break things into small, testable changes — that’s my comfort zone when tuning DBs on s390x. First, understand the platform: s390x is big-endian, so any extension or custom C code that assumes little-endian might misbehave; keep an eye on portability warnings when compiling extensions. Next I profile to find the real bottleneck: CPU-bound queries, index scans, or IO-bound workloads. pg_stat_statements is your friend for query hotspots.

Then I attack the low-hanging fruit. For IO-heavy databases, increase wal_compression if WAL volume is high; raise max_wal_size (or its older equivalent checkpoint_segments) so checkpoints don’t thrash the disks. Set synchronous_commit according to your durability needs — asynchronous for faster commits if you can accept a small window of data loss. Use autovacuum tuning aggressively on high-write tables (lower thresholds and increase workers) and consider tools like 'pg_repack' to reclaim bloat without long locks. Experiment with parallel settings: max_parallel_workers_per_gather and max_worker_processes can exploit many s390x cores but keep an eye on memory per worker.

Don’t forget OS-level tuning: disable swapping for the DB process, increase file descriptor limits, tune the block device queue depth if your storage supports it, and test different filesystems (XFS typically scales well). Finally, setup a staged rollout of changes: apply one change, run a representative workload, collect metrics, and only then proceed. It keeps surprises to a minimum and helps you learn which knobs actually move the needle.
2026-07-29 22:44:07
19
KiraRowe
KiraRowe
Bookworm Firefighter
A key difference is the I/O subsystem parallelism. On many s390x setups, you have multiple paths to storage. Ensure your multipath I/O configuration is optimal and that PostgreSQL is seeing a single, correctly aligned device. The readahead settings for your block devices might be too low for large sequential scans common in reporting queries; tune the readahead kernel parameter for your database volumes.

Also, look at the filesystem's journaling mode. For a database, having the filesystem journal metadata only (data=ordered or data=journal for ext4) is usually enough and reduces write overhead. For WAL and data on separate physical volumes, which you should absolutely do, ensure the filesystem mount options (like noatime, nodiratime) are set on both. And don't forget about the commit latency. If you need ultra-low latency commits, test with synchronouscommit = on and a battery-backed write cache on your storage controller—it's often a game-changer.
2026-07-30 14:50:03
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7 Answers2025-09-03 15:26:25
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