Received: from malur.postgresql.org ([217.196.149.56]) by arkaria.postgresql.org with esmtps (TLS1.3:ECDHE_RSA_AES_256_GCM_SHA384:256) (Exim 4.92) (envelope-from ) id 1pjxFP-0007sZ-0Z for pgsql-admin@arkaria.postgresql.org; Wed, 05 Apr 2023 07:07:59 +0000 Received: from localhost ([127.0.0.1] helo=malur.postgresql.org) by malur.postgresql.org with esmtp (Exim 4.92) (envelope-from ) id 1pjxFN-0008CX-Jl for pgsql-admin@arkaria.postgresql.org; Wed, 05 Apr 2023 07:07:57 +0000 Received: from makus.postgresql.org ([2001:4800:3e1:1::229]) by malur.postgresql.org with esmtps (TLS1.3:ECDHE_RSA_AES_256_GCM_SHA384:256) (Exim 4.92) (envelope-from ) id 1pjxFN-0008CI-7S for pgsql-admin@lists.postgresql.org; Wed, 05 Apr 2023 07:07:57 +0000 Received: from sender4-zc7.zoho.com ([136.143.188.7] helo=sender4.zoho.com) by makus.postgresql.org with esmtps (TLS1.3:ECDHE_RSA_AES_256_GCM_SHA384:256) (Exim 4.92) (envelope-from ) id 1pjxFG-00011e-S0 for pgsql-admin@lists.postgresql.org; Wed, 05 Apr 2023 07:07:56 +0000 ARC-Seal: i=1; a=rsa-sha256; t=1680678467; cv=none; d=zohomail.com; s=zohoarc; b=farKW5CzbMe/A9U0wz+5ykKolImUk0TETIfgqO2Udac/fZ1YlzxsyaIQUjbpbfkaQ9sayKFS8H5cnTso1nSaWygsZ1mhI0uHWthDbElVo9DW0ZR3Ga4d/620rZ9WHMcA8z05px0sMTwq6e7lwzbjiteGAYpNTl6ehBDMR3i2yVk= ARC-Message-Signature: i=1; a=rsa-sha256; c=relaxed/relaxed; d=zohomail.com; s=zohoarc; t=1680678467; h=Content-Type:Date:From:MIME-Version:Message-ID:Subject:To; bh=Fq+qtWuEIvHFUBlBegqZtT/exVoUjhcBIsZsq33Ob20=; b=NurZm0wN6h3IxwDJOolv8es3GgSSnAqIIO80LffGVWQ5+Wht5LPk6uUCD6+DTfM6ZjOclyL8ZP5IvwUHrUVAkfG4c3kE0zkuOpR+sUqL2n9NHTTaI7FMK4LRXDuVgVkx4o0DgtduGMm2047p47qu0wdrfB0X8vNCOgbYNsCWjdY= ARC-Authentication-Results: i=1; mx.zohomail.com; dkim=pass header.i=zohocorp.com; spf=pass smtp.mailfrom=karthikk@zohocorp.com; dmarc=pass header.from= DKIM-Signature: v=1; a=rsa-sha256; q=dns/txt; c=relaxed/relaxed; t=1680678467; s=admin; d=zohocorp.com; i=karthikk@zohocorp.com; h=Date:Date:From:From:To:To:Message-Id:Message-Id:In-Reply-To:Subject:Subject:MIME-Version:Content-Type:Reply-To:Cc; bh=Fq+qtWuEIvHFUBlBegqZtT/exVoUjhcBIsZsq33Ob20=; b=tNzIIfl5Q1f5eXxGpU8xIZBdt8eXiMVOFNmWK3N+4mgPu2k+BmvgLt1vY8zrz+Tt blYVqf+dPQVi6A3sU1RjKibnrR3XDpm7c6qpm9gCeYNrIJRUWYlUEhaArdA5EFRd2ds rwwbYIvgksNXAxxq2T5tN4o8J23Ywpv8pWZt67do= Received: from mail.zoho.com by mx.zohomail.com with SMTP id 1680678461287551.3000304046146; Wed, 5 Apr 2023 00:07:41 -0700 (PDT) Date: Wed, 05 Apr 2023 12:37:41 +0530 From: Karthik Krishnakumar To: "pgsql-admin" Message-Id: <18750398329.1002ca2ba316.8870907212977424118@zohocorp.com> In-Reply-To: Subject: Max tables in a cluster? MIME-Version: 1.0 Content-Type: multipart/alternative; boundary="----=_Part_953_543013687.1680678159145" Importance: Medium User-Agent: Zoho Mail X-Mailer: Zoho Mail List-Id: List-Help: List-Subscribe: List-Post: List-Owner: List-Archive: Archived-At: Precedence: bulk ------=_Part_953_543013687.1680678159145 Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: 7bit Hi admins, Is there a limit to number of tables that a cluster can support? At the moment, one of my clusters has about 250k user tables (plus 150k toast tables) across a hundred schemas within a single database. My application team wants to double the number of schemas (and with it the tables) I am looking for both pros and cons of doing this and what tuning can help this cluster perform acceptably. My questions are 1. Is there a limit to number of tables a cluster can support effectively? 2. My guess is autovacuum would have to be tuned. Current gucs for this are max_autovacuum_workers = 6 maintenance_work_mem = 1GB autovacuum_vacuum_scale_factor = 0.2 autovacuum_vacuum_cost_delay = 20ms Are there any potential problems that I need to think about ? My machine specs are as below. RAM 256GB 32-core CPU 7TB SSD thanks karthik ------=_Part_953_543013687.1680678159145 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable =
Hi admins,
<= br>
Is there a limit to number of tables that a cluster can suppo= rt?
At the moment, one of my clusters has about 250k user ta= bles (plus 150k toast tables) across a hundred schemas within a single data= base.
My application team wants to double the number of sche= mas (and with it the tables)
I am looking for both pros and c= ons of doing this and what tuning can help this cluster perform acceptably.=

My questions are
1. Is there = a limit to number of tables a cluster can support effectively?
2. My guess is autovacuum would have to be tuned. Current gucs for this a= re
max_autovacuum_workers =3D 6
maintenance_wo= rk_mem =3D 1GB
autovacuum_vacuum_scale_factor =3D 0.2
autovacuum_vacuum_cost_delay =3D 20ms

A= re there any potential problems that I need to think about ?
=
My machine specs are as below.
RAM 256GB
32-core CPU
7TB SSD

tha= nks
karthik

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