---
title: hyperloglog() | Tiger Data Docs
description: Aggregate data into a hyperloglog for approximate counting
---

Since [1.3.0](https://github.com/timescale/timescaledb-toolkit/releases/tag/1.3.0)

This is the first step for estimating the approximate number of distinct values using the `hyperloglog` algorithm. Use `hyperloglog` to create an intermediate aggregate from your raw data. This intermediate form can then be used by one or more accessors in this group to compute final results.

Optionally, multiple such intermediate aggregate objects can be combined using [`rollup()`](/docs/reference/toolkit/approximate-count-distinct/rollup/index.md) before an accessor is applied.

If you’re not sure what value to set for `buckets`, try using the alternate aggregate function, [`approx_count_distinct()`](/docs/reference/toolkit/approximate-count-distinct/approx_count_distinct/index.md). `approx_count_distinct` also creates a `hyperloglog`, but it sets a default bucket value that should work for many use cases.

## Samples

Given a table called `samples`, with a column called `weights`, return a `hyperloglog` over the `weights` column.

```
SELECT hyperloglog(32768, weights) FROM samples;
```

Using the same data, build a view from the aggregate that you can pass to other `hyperloglog` functions.

```
CREATE VIEW hll AS SELECT hyperloglog(32768, data) FROM samples;
```

## Arguments

The syntax is:

```
hyperloglog(
    buckets INTEGER,
    value AnyElement
) RETURNS Hyperloglog
```

| Name      | Type       | Default | Required | Description                                                                                                                                                                                                                                                                                                                                                                                                                     |
| --------- | ---------- | ------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `buckets` | INTEGER    | -       | ✔        | Number of buckets in the hyperloglog. Increasing the number of buckets improves accuracy but increases memory use. Value is rounded up to the next power of 2, and must be between 2^4 (16) and 2^18. Setting a value less than 2^10 (1,024) may result in poor accuracy if the true cardinality is high and is not recommended. If unsure, start experimenting with 8,192 (2^13) which has an approximate error rate of 1.15%. |
| `value`   | AnyElement | -       | ✔        | The column containing the elements to count. The type must have an extended, 64-bit, hash function.                                                                                                                                                                                                                                                                                                                             |

## Returns

| Column      | Type        | Description                                                                                            |
| ----------- | ----------- | ------------------------------------------------------------------------------------------------------ |
| hyperloglog | Hyperloglog | A `hyperloglog` object which can be passed to other hyperloglog APIs for rollups and final calculation |