# read_csv

Read CSV (Comma-Separated Values) from a byte stream.

```tql
read_csv [list_separator=string, null_value=string, comments=bool, header=string,
          quotes=string, auto_expand=bool, auto_fill=bool,
          schema=string, selector=string, schema_only=bool, raw=bool, unflatten_separator=string]
```

## Description

The `read_csv` operator transforms a byte stream into a event stream by parsing the bytes as [CSV](https://en.wikipedia.org/wiki/Comma-separated_values).

### `auto_expand = bool (optional)`

Automatically add fields to the schema when encountering events with too many values instead of dropping the excess values.

### `auto_fill = bool (optional)`

Silently fill missing trailing values in a row with `null` instead of emitting a warning. The missing fields are already filled with `null` either way; this option only suppresses the warning.

### `comments = bool (optional)`

Treat lines beginning with ”#” as comments.

### `header = list<string>|string (optional)`

A list of strings to be used as the column names, or a `string` to be parsed as the `header` for the parsed values. If unspecified, the first line of the input is used as the header.

### `list_separator = string (optional)`

The `string` separating the elements *inside* a list. If this string is found outside of quotes in a field, that field will become a list. If this string is empty, list parsing is disabled.

Defaults to `;`.

### `null_value = string (optional)`

The `string` denoting an absent value.

Defaults to empty string (`""`).

### `quotes = string (optional)`

A string of not escaped characters that are supposed to be considered as quotes.

Defaults to the characters `"'`.

### `merge = bool (optional)`

Merges all incoming events into a single schema\* that converges over time. This option is usually the fastest *for reading* highly heterogeneous data, but can lead to huge schemas filled with nulls and imprecise results. Use with caution.

\*: In selector mode, only events with the same selector are merged.

In merging mode, a repeated key will always overwrite the previous value.

### `raw = bool (optional)`

Use only the raw types that are native to the parsed format. Fields that have a type specified in the chosen `schema` will still be parsed according to the schema.

### `schema = string (optional)`

Provide the name of a schema to be used by the parser.

If a schema with a matching name is installed, the result will always have all fields from that schema.

* Fields that are specified in the schema, but did not appear in the input will be null.
* Fields that appear in the input, but not in the schema will also be kept. Use `schema_only=true` to reject fields that are not in the schema.

If the given schema does not exist, this option instead assigns the output schema name only.

The `schema` option is incompatible with the `selector` option.

### `selector = string (optional)`

Designates a field value as schema name with an optional dot-separated prefix.

The string is parsed as `<fieldname>[:<prefix>]`. The `prefix` is optional and will be prepended to the field value to generate the schema name.

For example, the Suricata EVE JSON format includes a field `event_type` that contains the event type. Setting the selector to `event_type:suricata` causes an event with the value `flow` for the field `event_type` to map onto the schema `suricata.flow`.

The `selector` option is incompatible with the `schema` option.

### `schema_only = bool (optional)`

When working with an existing schema, this option will ensure that the output schema has *only* the fields from that schema.

If the schema name is obtained via a `selector` and it does not exist, this has no effect.

This option requires either `schema` or `selector` to be set.

### `unflatten_separator = string (optional)`

A delimiter that, if present in keys, causes values to be treated as values of nested records.

A popular example of this is the [Zeek JSON](https://preview.docs.tenzir.com/375/375/reference/operators/read_zeek_json.md) format. It includes the fields `id.orig_h`, `id.orig_p`, `id.resp_h`, and `id.resp_p` at the top-level. The data is best modeled as an `id` record with four nested fields `orig_h`, `orig_p`, `resp_h`, and `resp_p`.

Without an unflatten separator, the data looks like this:

Without unflattening

```json
{
  "id.orig_h": "1.1.1.1",
  "id.orig_p": 10,
  "id.resp_h": "1.1.1.2",
  "id.resp_p": 5
}
```

With the unflatten separator set to `.`, Tenzir reads the events like this:

With 'unflatten'

```json
{
  "id": {
    "orig_h": "1.1.1.1",
    "orig_p": 10,
    "resp_h": "1.1.1.2",
    "resp_p": 5
  }
}
```

### Duplicate Keys

If the parser encounters a duplicate key in an event, it will transparently upgrade the field to be a list of values instead.

For a simple example, consider this JSON file:

Duplicate Keys

```json
{"key": 7}
{"key": 0.0, "key": 1}
{"key": 42}
```

```tql
{key: 7}
{key: [0.0, 1.0]}
{key: 42}
```

If the values are of different type, conversions to a common type will be attempted, such as to a common number type. Ultimately values will be stringified if they do not share a common type:

Type Conflict

```json
{"key": 0.0, "key": "1.1.1.1", "key": "example.com"}
```

```tql
{key: ["0", "1.1.1.1", "example.com"]}
```

## Examples

### Read a CSV file with header

input.csv

```txt
message,count,ip
some text,42,"1.1.1.1"
more text,100,"1.1.1.2"
```

```tql
load "input.csv"
read_csv
```

```tql
{message: "some text", count: 42, ip: 1.1.1.1}
{message: "more text", count: 100, ip: 1.1.1.2}
```

### Manually specify a header

input\_no\_header.csv

```txt
some text,42,"1.1.1.1"
more text,100,"1.1.1.2"
```

```tql
load "input_no_header.csv"
read_csv header="message,count,ip"
```

```tql
{message: "some text", count: 42, ip: 1.1.1.1}
{message: "more text", count: 100, ip: 1.1.1.2}
```

## See Also

* [`parse_csv`](https://preview.docs.tenzir.com/375/375/reference/functions/parse_csv.md)
* [`print_csv`](https://preview.docs.tenzir.com/375/375/reference/functions/print_csv.md)
* [`read_ssv`](https://preview.docs.tenzir.com/375/375/reference/operators/read_ssv.md)
* [`read_tsv`](https://preview.docs.tenzir.com/375/375/reference/operators/read_tsv.md)
* [`read_xsv`](https://preview.docs.tenzir.com/375/375/reference/operators/read_xsv.md)
* [`write_csv`](https://preview.docs.tenzir.com/375/375/reference/operators/write_csv.md)
* [Convert data formats](https://preview.docs.tenzir.com/375/375/guides/transformation/convert-data-formats.md)