Speed up creation of Postgres partial index I am trying to create partial indexes for a large (1.2TB), static table in Postgres 9.4.

My data is completely static, so I am able to insert all data, then create all indexes.

In this 1.2TB table, I have a column named run_id that cleanly divides the data. We've gotten great performance by creating indexes that cover a range of run_ids. Here's an example:

CREATE INDEX perception_run_frame_idx_run_266_thru_270
ON run.perception
(run_id, frame)
WHERE run_id &gt;= 266 AND run_id &lt;= 270;


These partial indexes give us the desired query speed. Unfortunately, the creation of each partial index takes about 70 minutes.

It looks like we are CPU limited (top is showing 100% for the process).
Is there anything I can do to speed up the creation of our partial indexes? 

System specs:


18 core Xeon
192GB RAM
12 SSDs in RAID
Autovacuums are turned OFF
maintenance_work_mem: 64GB (Too high?)


Table specs:


Size: 1.26 TB
Number of rows: 10.537 Billion
Typical index size: 3.2GB (there is a ~.5GB variance)


Table definition:

CREATE TABLE run.perception(
id bigint NOT NULL,
run_id bigint NOT NULL,
frame bigint NOT NULL,
by character varying(45) NOT NULL,
by_anyone bigint NOT NULL,
by_me bigint NOT NULL,
by_s_id integer,
owning_p_id bigint NOT NULL,
obj_type_set bigint,
seq integer,
subj_id bigint NOT NULL,
subj_state_frame bigint NOT NULL,
CONSTRAINT perception_pkey PRIMARY KEY (id))


(Don't read too much into the column names -- I've obfuscated them somewhat.)

Background info:


We have a separate team onsite that consumes this data, but really there are only one or two users. (This data is all generated via a simulation.) Users only start analyzing the data once inserts are finished and indexes are completely built. Our main concern is reducing the time required to generate usable data, and right now the bottleneck is index creation time.
Query speed has been completely adequate when using partials. In fact, I think we could increase the number of runs that each index covers, and still maintain good-enough query performance.
My guess is that we will have to partition the table. We are trying to exhaust all other options before taking that route.
BRIN index

Available since Postgres 9.5 and probably just what you are looking for. Much faster index creation, much smaller index. But queries are typically not as fast. The manual:


  BRIN stands for Block Range Index. BRIN is designed for handling very
  large tables in which certain columns have some natural correlation
  with their physical location within the table. A block range is a
  group of pages that are physically adjacent in the table; for each
  block range, some summary info is stored by the index.


Read on, there is more.
Depesz ran a preliminiary test.

The optimum for your case: If you can write rows clustered on run_id, your index becomes very small and creation much cheaper. 

CREATE INDEX foo ON run.perception USING brin (run_id, frame)
WHERE run_id &gt;= 266 AND run_id &lt;= 270;


You might even just index the whole table.

Table layout

Whatever else you do, you can save 8 bytes lost to padding due to alignment requirements per row by ording columns like this:

CREATE TABLE run.perception(
  id               bigint NOT NULL PRIMARY KEY
, run_id           bigint NOT NULL
, frame            bigint NOT NULL
, by_anyone        bigint NOT NULL
, by_me            bigint NOT NULL
, owning_p_id      bigint NOT NULL
, subj_id          bigint NOT NULL
, subj_state_frame bigint NOT NULL
, obj_type_set     bigint
, by_s_id          integer
, seq              integer
, by               varchar(45) NOT NULL -- or just use type text
);


Makes your table 79 GB smaller if none of the columns has NULL values. Details:


Configuring PostgreSQL for read performance


Also, you only have three columns that can be NULL. The NULL bitmap occupies 8 bytes for 9 - 72 columns. If only one integer column is NULL, there is a corner case for a storage paradox: it would be cheaper to use a dummy value instead: 4 bytes wasted but 8 bytes saved by not needing a NULL bitmap for the row. More details here:


How do completely empty columns in a large table affect performance?


Partial indexes

Depending on your actual queries it might be more efficient to have these five partial indices instead of the one above:

CREATE INDEX perception_run_id266_idx ON run.perception(frame) WHERE run_id = 266;
CREATE INDEX perception_run_id266_idx ON run.perception(frame) WHERE run_id = 267;
CREATE INDEX perception_run_id266_idx ON run.perception(frame) WHERE run_id = 268;
CREATE INDEX perception_run_id266_idx ON run.perception(frame) WHERE run_id = 269;
CREATE INDEX perception_run_id266_idx ON run.perception(frame) WHERE run_id = 270;


Run one transaction for each.

Removing run_id as index column this way saves 8 bytes per index entry - 32 instead of 40 bytes per row. Each index is also cheaper to create, but creating five instead of just one takes substantially longer for a table that's too big to stay in cache (like @Jürgen and @Chris commented). So that may or may not be useful for you.

Partitioning

Based on inheritance - the only option up to Postgres 9.5.
(The new declarative partitioning in Postgres 11 or, preferably, 12 is smarter.)

The manual:


  All constraints on all children of the parent table are examined
  during constraint exclusion, so large numbers of partitions are likely
  to increase query planning time considerably. So the legacy inheritance
  based partitioning will work well with up to perhaps a hundred partitions;
  don't try to use many thousands of partitions.


Bold emphasis mine. Consequently, estimating 1000 different values for run_id, you would make partitions spanning around 10 values each.



maintenance_work_mem

I missed that you are already adjusting for maintenance_work_mem in my first read. I'll leave quote and advice in my answer for reference. Per documentation:


  maintenance_work_mem (integer)
  
  Specifies the maximum amount of memory to be used by maintenance
  operations, such as VACUUM, CREATE INDEX, and ALTER TABLE ADD FOREIGN KEY. It defaults to 64 megabytes (64MB). Since only one of these
  operations can be executed at a time by a database session, and an
  installation normally doesn't have many of them running concurrently,
  it's safe to set this value significantly larger than work_mem. Larger
  settings might improve performance for vacuuming and for restoring
  database dumps.
  
  Note that when autovacuum runs, up to autovacuum_max_workers times this memory may be allocated, so be careful not to set the default
  value too high. It may be useful to control for this by separately
  setting autovacuum_work_mem.


I would only set it as high as needed - which depends on the unknown (to us) index size. And only locally for the executing session. As the quote explains, a too-high general setting can starve the server otherwise, because autovacuum may claim more RAM, too. Also, don't set it much higher than needed, even in the executing session, free RAM might be put to good use in caching data.

It could look like this:

BEGIN;

SET LOCAL maintenance_work_mem = 10GB;  -- depends on resulting index size

CREATE INDEX perception_run_frame_idx_run_266_thru_270 ON run.perception(run_id, frame)
WHERE run_id &gt;= 266 AND run_id &lt;= 270;

COMMIT;

About SET LOCAL: 


  The effects of SET LOCAL last only till the end of the current
  transaction, whether committed or not.


To measure object sizes:


Measure the size of a PostgreSQL table row


The server should generally be configured reasonably otherwise, obviously.