---
title: Read Throughput
description: Settings to improve read performance
canonical: https://www.paradedb.com/docs/operate/performance-tuning/reads
---

As a general rule of thumb, the performance of expensive search queries can be greatly improved
if they are able to access more parallel Postgres workers and more shared buffer memory.

## Increasing Parallel Workers

There are three settings that control how many parallel workers ultimately get assigned to a query.

First, `max_worker_processes` is a global limit for the number of workers.
Next, `max_parallel_workers` is a subset of `max_worker_processes`, and sets the limit for workers used in
parallel queries. Finally, `max_parallel_workers_per_gather` limits how many workers a _single query_ can receive.

```ini postgresql.conf
max_worker_processes = 72
max_parallel_workers = 64
max_parallel_workers_per_gather = 4
```

In the above example, the maximum number of workers that a single query can receive is set to `4`. The `max_parallel_workers` pool
is set to `64`, which means that `16` queries can execute simultaneously with `4` workers each. Finally, `max_worker_processes` is
set to `72` to give headroom for other workers like autovacuum and replication.

This is a good starting point:

```ini postgresql.conf
max_parallel_workers = 5 * CPUs
max_worker_processes = max_parallel_workers + 8
max_parallel_workers_per_gather = CPUs / 2
```

We recommend experimenting with different settings, as the best configuration depends on the underlying hardware,
query patterns, and volume of data.

<Note>
  If all `max_parallel_workers` are in use, Postgres will still execute
  additional queries, but those queries will run without parallelism. This means
  that queries do not fail, but they may run slower due to lack of parallelism.
</Note>

## Increasing Shared Buffers

`shared_buffers` controls how much memory is available to the Postgres buffer cache. We recommend starting with 25% of total memory for `shared_buffers` and no more than 40% of total memory.

```ini postgresql.conf
shared_buffers = 8GB
```

The `pg_prewarm` extension can be used to load the ParadeDB index into the buffer cache after Postgres restarts. A higher `shared_buffers` value allows more of the index to be
stored in the buffer cache.

```sql
CREATE EXTENSION pg_prewarm;
SELECT pg_prewarm('search_idx');
```

## Configuring Autovacuum

If an index experiences frequent writes, the search performance of some queries like [sorting](/reference/full-text/score) or
[aggregates](/reference/aggregates/overview) can degrade if `VACUUM` has not been recently run. This is because writes can cause parts of Postgres' visibility map
to go out of date, and `VACUUM` updates the visibility map.

To determine if search performance is degraded by lack of `VACUUM`, run `EXPLAIN ANALYZE` over a query. A `Parallel Custom Scan`
in the query plan with a large number of `Heap Fetches` typically means that `VACUUM` should be run.

Postgres can be configured to automatically vacuum a table when a certain number of rows have been updated. Autovacuum settings
can be set globally in `postgresql.conf` or for a specific table.

```sql
ALTER TABLE mock_items SET (autovacuum_vacuum_threshold = 500);
```

There are several [autovacuum settings](https://www.postgresql.org/docs/current/routine-vacuuming.html#AUTOVACUUM), but the important ones to
note are:

1. `autovacuum_vacuum_scale_factor` triggers an autovacuum if a certain percentage of rows in a table have been updated.
2. `autovacuum_vacuum_threshold` triggers an autovacuum if an absolute number of rows have been updated.
3. `autovacuum_naptime` ensures that vacuum does not run too frequently.

This means that setting `autovacuum_vacuum_scale_factor` to `0` and `autovacuum_vacuum_threshold` to `100000` will trigger an autovacuum
for every `100000` row updates. As a general rule of thumb, we recommend autovacuuming at least once every `100000` single-row updates.

## Adjusting Target Segment Count

By default, `CREATE INDEX`/`REINDEX` will create as many segments as there are CPUs on the host machine. This can be changed using the
`target_segment_count` index option.

```sql
CREATE INDEX search_idx ON mock_items USING paradedb (id, description, rating) WITH (key_field = 'id', target_segment_count = 32, ...);
```

This property is attached to the index so that during `REINDEX`, the same value will be used.

It can be changed with ALTER INDEX, like so:

```sql
ALTER INDEX search_idx SET (target_segment_count = 8);
```

However, a `REINDEX` is required to rebalance the index to that segment count.

For optimal performance, the segment count should equal the number of parallel workers that a query can receive, which is controlled by
[`max_parallel_workers_per_gather`](/operate/performance-tuning/reads#increasing-parallel-workers). If `max_parallel_workers_per_gather` is greater than the number of CPUs on the host machine, then increasing the target segment count to match `max_parallel_workers_per_gather` can improve query
performance.

<Note>
  Actual segment counts may vary depending on parallel builder distribution, memory limits, and table size.

When partitioning an index with [`partition_by`](/reference/indexing/partition-by), we recommend setting `target_segment_count` to 2–4X `max_parallel_workers_per_gather` (or CPU count). Creating more segments allows ParadeDB to skip more non-matching data during filtered queries and better align partition ranges across tables during parallel joins.

</Note>