---
title: "geomean"
slug: "dev-database-reference-sql-functions-aggregate-geomean"
updated: 2026-10-30T18:18:46Z
published: 2026-10-30T18:18:46Z
canonical: "docs.vastdata.com/dev-database-reference-sql-functions-aggregate-geomean"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vastdata.com/llms.txt
> Use this file to discover all available pages before exploring further.

# geomean

*Applies to VAST Cluster 5.5.*

*[Functions](/develop/docs/dev-database-reference-sql-functions-index) › [Aggregate and analytic functions](/develop/docs/dev-database-reference-sql-functions-aggregate) › Sums and averages.* Returns the geometric mean of positive values: the n-th root of the product of n values. `geometric_mean` is the same function.

## Syntax

```
geomean(x)
geometric_mean(x)
```

| Argument | Type | Description |
| --- | --- | --- |
| `x` | a number: any integer type, `FLOAT`, `DOUBLE` or `DECIMAL` | The values. Every non-NULL value must be greater than 0. |

**Returns:** `DOUBLE`.

**Aliases:** `geometric_mean`.

## Set up the examples

The examples connect with the ADBC driver, as in [VAST Query Engine (ADBC)](/develop/docs/dev-database-integrations-adbc), and work in a schema called `docs_sql_fn_aggregate_geomean`. Set `QE_ENDPOINT`, `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY` and `VASTDB_BUCKET` ([SQL reference](/develop/docs/dev-database-reference-sql-index#example-connect-and-use-a-transaction)), and run the blocks in order in one Python session. Below each block is the output you should see.

This block connects, defines the `run()` and `plan()` helpers, and creates a table of four years of a fund: its growth factor that year (1.10 is 10% up), the same change as a fraction (0.10), and the number of new investors. The last year has no growth figures yet, and no new investors:

```
import os
import re

import adbc_driver_manager
import adbc_driver_manager.dbapi as dbapi
import adbc_driver_vastdb

BUCKET = os.environ["VASTDB_BUCKET"]
SCHEMA = f'"{BUCKET}/docs_sql_fn_aggregate_geomean"'

conn = dbapi.connect(
    driver=adbc_driver_vastdb.get_driver_path(),
    db_kwargs={
        "vast.db.endpoint": os.environ["QE_ENDPOINT"],
        "vast.db.access_key": os.environ["AWS_ACCESS_KEY_ID"],
        "vast.db.secret_key": os.environ["AWS_SECRET_ACCESS_KEY"],
    },
    autocommit=True,
)

def server_message(e):
    """The server's message in a driver error, without the request ID or the echoed statement."""
    text = re.sub(r"\[req=0x[0-9a-f]+\]: ", "", str(e))
    found = (re.search(r'message: "(.*?)", request_id', text, re.S)
             or re.search(r"description: (.*)\)", text, re.S))
    message = found.group(1) if found else text.strip().splitlines()[-1]
    message = re.sub(r"^Plan query: '.*?' failed with: ", "", message, flags=re.S)
    message = re.split(r"\\n|\n", message)[0].replace('\\"', '"')
    return message.replace(BUCKET, "<bucket>")

def run(sql):
    """Run one statement. Print the rows it returns, or the error."""
    try:
        with conn.cursor() as cur:
            cur.execute(sql)
            rows = cur.fetchall() if cur.description else []
    except (adbc_driver_manager.Error, OSError) as e:
        print(f"{type(e).__name__}: {server_message(e)}")
    else:
        print(rows)

def plan(sql):
    """Print the plan without its ~N Rows lines: the table's row count, which can still be 0 just after an insert."""
    with conn.cursor() as cur:
        cur.execute("EXPLAIN " + sql)
        steps = cur.fetchall()[0][1]
    print("\n".join(line for line in steps.splitlines() if "Rows" not in line))

TABLE = f"{SCHEMA}.fund_years"
run(f"CREATE SCHEMA IF NOT EXISTS {SCHEMA}")
run(f"CREATE TABLE IF NOT EXISTS {TABLE} (id BIGINT, factor DOUBLE, change DOUBLE, investors INTEGER)")
run(f"INSERT INTO {TABLE} VALUES "
    "(1, 1.10, 0.10, 2), "
    "(2, 0.95, -0.05, 8), "
    "(3, 1.20, 0.20, 4), "
    "(4, NULL, NULL, 0)")
```

```
[]
[]
[(4,)]
```

## What it does

`geomean(x)` is an aggregate: it returns the n-th root of the product of the n non-NULL values of `x`. It's the right mean for factors that multiply, such as yearly growth rates: the geometric mean of the yearly factors is the constant yearly factor that gives the same total growth.

The plan shows how it's computed, through logarithms:

```
exp(avg(ln(x)))
```

So the rules of [ln](/develop/docs/dev-database-reference-sql-functions-numeric-ln) apply to every value: **a zero or a negative value stops the query with an error**, `cannot take logarithm of zero` or `cannot take logarithm of a negative number`. Leave such rows out in `WHERE`, or measure growth as factors (1.10, 0.95), not as changes (0.10, -0.05), which can be negative.

NULLs are skipped, as by [avg](/develop/docs/dev-database-reference-sql-functions-aggregate-avg). `geomean` is a macro, a shorthand the Query Engine expands into that expression, not an aggregate of its own, so it can't take `FILTER`, `DISTINCT` or `ORDER BY` (see [Limitations and errors](/develop/docs/dev-database-reference-sql-functions-aggregate-geomean#limitations-and-errors)).

## NULLs and edge cases

| Input | Result |
| --- | --- |
| NULL values | Skipped |
| Only NULLs, or `geomean(NULL)` | NULL |
| No rows (an empty table, or a `WHERE` that matches nothing) | NULL |
| `geomean(2.5)` with no `FROM`, or one row | The value itself |
| A zero among the values | Error: `cannot take logarithm of zero` |
| A negative value among the values | Error: `cannot take logarithm of a negative number` |
| A string, date, time, timestamp, `BOOLEAN` or list | Error: `No function matches the given name and argument types`, naming `ln`, for example `&apos;ln(VARCHAR)&apos;` |
| `geomean(x) FILTER (WHERE ...)` | Error: `Function &quot;geomean&quot; is a Macro Function. &quot;DISTINCT&quot;, &quot;FILTER&quot;, and &quot;ORDER BY&quot; are only applicable to aggregate functions.` |

The same cases, as the cluster returns them. They use the table and helpers from [Set up the examples](/develop/docs/dev-database-reference-sql-functions-aggregate-geomean#set-up-the-examples):

```
run(f"SELECT geomean(factor), geometric_mean(factor) FROM {TABLE}")
run(f"SELECT geomean(factor) FROM {TABLE} WHERE id = 4")
run(f"SELECT geomean(factor) FROM {TABLE} WHERE id > 100")
run("SELECT geomean(NULL), geomean(2.5)")
run(f"SELECT geomean(investors) FROM {TABLE}")
run(f"SELECT geomean(change) FROM {TABLE}")
run(f"SELECT geomean(id > 1) FROM {TABLE}")
run(f"SELECT geomean(factor) FILTER (WHERE id < 3) FROM {TABLE}")
```

```
[(1.078365153390936, 1.078365153390936)]
[(None,)]
[(None,)]
[(None, 2.5)]
OSError: cannot take logarithm of zero
OSError: cannot take logarithm of a negative number
InternalError: Binder Error: No function matches the given name and argument types 'ln(BOOLEAN)'. You might need to add explicit type casts.
InternalError: Invalid Input Error: Function "geomean" is a Macro Function. "DISTINCT", "FILTER", and "ORDER BY" are only applicable to aggregate functions.
```

## Examples

The average yearly growth factor of the fund, next to the arithmetic mean of the same factors and the formula written out:

```
run(f"SELECT geomean(factor), avg(factor), exp(avg(ln(factor))) FROM {TABLE}")
```

```
[(1.078365153390936, 1.0833333333333333, 1.078365153390936)]
```

The geometric mean of the number of new investors, over the years that had any. The year with 0 is left out in `WHERE`, which runs before the aggregate:

```
run(f"SELECT geomean(investors) FROM {TABLE} WHERE investors > 0")
```

```
[(4.0,)]
```

The average yearly change from changes stored as fractions: add 1 to turn them into factors, and subtract 1 from the result:

```
run(f"SELECT geomean(1 + change) - 1 FROM {TABLE}")
```

```
[(0.07836515339093597,)]
```

## How it runs in VAST

The Query Engine runs on the cluster's CNodes. A `geomean` query has three steps, which [EXPLAIN](/develop/docs/dev-database-reference-sql-explain) shows:

1. **A scan in VAST DataBase** (`VAST_SCAN`), which reads the column and evaluates the `WHERE` conditions it can [push down](/develop/docs/dev-database-reference-pushdowns).
2. **One aggregate step** (`UNGROUPED_AGGREGATE`) in the Query Engine, which computes `avg(ln(x))` over the rows the scan sends.
3. **A `PROJECTION` step**, which applies `exp()` to the result.

The `WHERE` condition of the second example compares a column with a constant, so it's evaluated in the scan and doesn't appear in the plan:

```
plan(f"SELECT geomean(investors) FROM {TABLE} WHERE investors > 0")
```

```
┌───────────────────────────┐
│         PROJECTION        │
│    ────────────────────   │
│ exp(avg(ln(CAST(investors │
│        AS DOUBLE))))      │
│                           │
└─────────────┬─────────────┘
┌─────────────┴─────────────┐
│    UNGROUPED_AGGREGATE    │
│    ────────────────────   │
│        Aggregates:        │
│  avg(ln(CAST(investors AS │
│          DOUBLE)))        │
└─────────────┬─────────────┘
┌─────────────┴─────────────┐
│         VAST_SCAN         │
│    ────────────────────   │
│    Function: VAST_SCAN    │
│                           │
│        Projections:       │
│         investors         │
│                           │
└───────────────────────────┘
```

## Make it faster

- **Leave out zeros and negatives in `WHERE`.** `WHERE x &gt; 0` is pushed down to VAST DataBase, so those rows never leave storage, and the query doesn't fail on them.
- **Compute it with other aggregates in one query.** They share one scan.
- **Store factors rather than changes** if you often take their geometric mean: `geomean(factor)` reads the column as it is, while `geomean(1 + change)` computes `1 + change` on every row.

## Limitations and errors

- **Positive values only.** A zero or a negative value fails the whole query, not just that row. Filter them out, or shift the values (`geomean(x + 1) - 1` for changes), knowing that a shift changes the result.
- **No `FILTER`, `DISTINCT` or `ORDER BY`.** They fail with `Function &quot;geomean&quot; is a Macro Function. &quot;DISTINCT&quot;, &quot;FILTER&quot;, and &quot;ORDER BY&quot; are only applicable to aggregate functions.` (`geometric_mean` in the message when you use that name). Use `WHERE`, or write `exp(avg(ln(x)) FILTER (WHERE ...))` out.
- **No window form.** `geomean(x) OVER (...)` fails with `Catalog Error: exp is not an aggregate function`.
- **Numbers only.** A string, a date, a `BOOLEAN` or a list fails with `No function matches the given name and argument types`, and the message names `ln`, such as `&apos;ln(VARCHAR)&apos;`.
- **No `GROUP BY`.** A geometric mean per group fails with `The operator &apos;HASH_GROUP_BY&apos; type=9 is currently not supported.`

```
run(f"SELECT exp(avg(ln(factor)) FILTER (WHERE id < 3)) FROM {TABLE}")
run(f"SELECT id, geomean(factor) OVER (ROWS UNBOUNDED PRECEDING) FROM {TABLE}")
```

```
[(1.0222524150130436,)]
InternalError: Catalog Error: exp is not an aggregate function
```

## Similar functions

| Function | Returns |
| --- | --- |
| `geomean(x)`, `geometric_mean(x)` | the n-th root of the product of n positive values |
| `exp(avg(ln(x)))` ([exp](/develop/docs/dev-database-reference-sql-functions-numeric-exp), [ln](/develop/docs/dev-database-reference-sql-functions-numeric-ln), [avg](/develop/docs/dev-database-reference-sql-functions-aggregate-avg)) | the same value; it can also take `FILTER` |
| [avg](/develop/docs/dev-database-reference-sql-functions-aggregate-avg) `(x)` | the arithmetic mean, which is never lower than the geometric mean of the same positive values |
| [product](/develop/docs/dev-database-reference-sql-functions-aggregate-product) `(x)` | the product itself |
| [wavg](/develop/docs/dev-database-reference-sql-functions-aggregate-wavg) `(x, w)` | a weighted arithmetic mean |

```
run(f"SELECT geomean(factor), exp(avg(ln(factor))), avg(factor), product(factor), wavg(factor, 1) FROM {TABLE}")
```

```
[(1.078365153390936, 1.078365153390936, 1.0833333333333333, 1.2539999999999998, 1.0833333333333333)]
```

Clean up:

```
run(f"DROP TABLE IF EXISTS {TABLE}")
run(f"DROP SCHEMA IF EXISTS {SCHEMA}")
conn.close()
```

```
[]
[]
```

## See also

- [Aggregate and analytic functions](/develop/docs/dev-database-reference-sql-functions-aggregate): all the aggregates, and the ones that aren't available.
- [avg](/develop/docs/dev-database-reference-sql-functions-aggregate-avg), [product](/develop/docs/dev-database-reference-sql-functions-aggregate-product) and [ln](/develop/docs/dev-database-reference-sql-functions-numeric-ln).
- [Pushdowns](/develop/docs/dev-database-reference-pushdowns) and [EXPLAIN](/develop/docs/dev-database-reference-sql-explain).