---
title: "Trino data types and casts"
description: "Whatever path you take to query your project over Trino, the SQL editor of the Explorer, a Trino consumer, or an external tool"
url: https://docs.ovhcloud.com/pl/guides/public-cloud/data-platform/tutorials-trino-types-and-casts
lang: pl
lastUpdated: 2026-09-14
---
> For AI agents: the complete documentation index is available at https://docs.ovhcloud.com/pl/llms.txt, the full documentation bundle is available at https://docs.ovhcloud.com/pl/llms-full.txt.

# Trino data types and casts

## Objective

Whatever path you take to query your project over [Trino](https://trino.io/), the SQL editor of the [Explorer](https://docs.ovhcloud.com/pl/guides/public-cloud/data-platform/lakehouse-manager-explorer.md), a [Trino consumer](https://docs.ovhcloud.com/pl/guides/public-cloud/data-platform/connectors-consumers-trino.md), or an external tool, the types you manipulate are the **Trino types**, not the logical types you see in the [Lakehouse Manager](https://docs.ovhcloud.com/pl/guides/public-cloud/data-platform/lakehouse-manager-attributes.md). Most of the time the two line up, but a few cases require an explicit `CAST` at `INSERT` time.

## Data types: Lakehouse to Trino

The table below maps each Lakehouse type to the Trino type it is exposed as:

| Lakehouse type   | Trino type      | Notes                                         |
| ---------------- | --------------- | --------------------------------------------- |
| `integer`        | `INTEGER`       | 32-bit signed integer                         |
| `bigint`         | `BIGINT`        | 64-bit signed integer                         |
| `real` / `float` | `REAL`          | 32-bit floating point                         |
| `double`         | `DOUBLE`        | 64-bit floating point                         |
| `decimal`        | `DECIMAL(p, s)` | Precision and scale are preserved             |
| `varchar`        | `VARCHAR`       | Unbounded unless a length was set at creation |
| `boolean`        | `BOOLEAN`       |                                               |
| `date`           | `DATE`          |                                               |
| `timestamp`      | `TIMESTAMP`     | Timezone-naive                                |

:::info
The exact Trino type of a column, including any length or precision, is whatever the table was **created** with. When in doubt, run `SHOW CREATE TABLE <catalog>.<schema>.<table>;`. Any `CAST` in an `INSERT` should target that type, not the logical type you see in the Lakehouse Manager.
:::

### Implicit coercions (no CAST needed)

Trino widens these types automatically, so you can insert the source value directly:

- `INTEGER` → `BIGINT`
- `REAL` → `DOUBLE`
- `DECIMAL` → a wider `DECIMAL`
- `VARCHAR(n)` → unbounded `VARCHAR`: a literal such as `'foo'` is a `VARCHAR(3)` and coerces to an Iceberg string without any change
- `DATE` → `TIMESTAMP`

### Casts you must write explicitly

Trino will **not** coerce these on its own. An `INSERT` without a `CAST` returns `TYPE_MISMATCH`:

- `VARCHAR` → numeric or date: `CAST('1' AS INTEGER)`, `CAST('2026-05-26' AS DATE)`
- numeric → `VARCHAR`: `CAST(x AS VARCHAR)`
- `TIMESTAMP` ↔ `TIMESTAMP WITH TIME ZONE` (any change in timezone-awareness)
- `DECIMAL(p1, s1)` → `DECIMAL(p2, s2)` when the precision or scale differs and truncation is possible
- Complex types: there is no coercion between `ROW` values of different structures, you have to rebuild the `ROW(...)` field by field

## Inserting typed values

### Use a valid literal form

`INT '1'` is **not** valid Trino syntax. `INT` is accepted as an alias of `INTEGER` in a _column declaration_, but not in the _typed-literal_ form `TYPE 'value'`.

To insert an integer, use any of:

```sql
INSERT INTO t VALUES (1);                    -- native integer literal
INSERT INTO t VALUES (INTEGER '1');          -- typed literal, canonical type name
INSERT INTO t VALUES (CAST('1' AS INTEGER)); -- explicit cast
```

:::info
Reading the same column never raises an error, because no typed literal is evaluated on `SELECT`. Only the `INT 'x'` form breaks the parser.
:::

### Troubleshooting TYPE\_MISMATCH on VARCHAR inserts

`CAST(x AS VARCHAR)` produces an unbounded `VARCHAR`, which is compatible with an Iceberg string column. If you still get a `TYPE_MISMATCH`, check the following, in order:

1. **The target column may not be unbounded.** If the table was created through Trino with `VARCHAR(50)`, the connector keeps that length constraint. Confirm with `DESCRIBE catalog.schema.table;` or `SHOW CREATE TABLE catalog.schema.table;`. If the column is `varchar(50)`, cast to `CAST(x AS VARCHAR(50))`.
2. **Column order or count.** Without an explicit column list, Trino maps values by position and raises `TYPE_MISMATCH` as soon as one downstream column no longer matches, and the error sometimes points at the wrong expression. Always prefer:
   ```sql
   INSERT INTO t (col_a, col_b, col_c) VALUES (...);
   ```
3. **Complex types.** `CAST(... AS VARCHAR)` on a `ROW`, `ARRAY` or `MAP` fails. Convert field by field, or use `json_format(CAST(... AS JSON))`.
4. **Generated columns and timestamps.** A `VARCHAR` does not coerce implicitly to `TIMESTAMP` or `DATE`. A `TYPE_MISMATCH` that appears to be on a `VARCHAR` can actually come from another column in the same `VALUES` clause.

:::warning
If the mismatch persists, collect `SHOW CREATE TABLE`, the full `INSERT` statement and the exact error message before opening a support ticket. That is enough to pinpoint the faulty column.
:::

## Go further

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