CSV import via REST API

The REST API provides an /imp endpoint exposed on port 9000 by default. This endpoint allows streaming tabular text data directly into a table, supporting CSV, TAB and pipe (|) delimited inputs with optional headers. Data types and structures are detected automatically, but additional configuration can be provided to improve automatic detection.

note

The REST API is better suited for regular uploads of small batches of data via CSV files into the same table. For database migrations with large CSV files of un-ordered data, The COPY SQL command is recommended instead. See COPY command documentation and Guide on CSV import for more details.

Specifying a schema during CSV import#

A schema JSON object can be provided with POST requests to /imp while creating tables via CSV import. This allows for more control over user-defined patterns for timestamps, or for explicitly setting types during column-creation. The the following example demonstrates basic usage, in this case, that the ticker_name column should be parsed as SYMBOL type instead of STRING:

curl \
-F schema='[{"name":"ticker_name", "type": "SYMBOL"}]' \
-F data=@trades.csv 'http://localhost:9000/imp'

If a timestamp column (ts) in this CSV file has a custom or non-standard timestamp format, this may be included with the call as follows:

curl \
-F schema='[ \
{"name":"ts", "type": "TIMESTAMP", "pattern": "yyyy-MM-dd - HH:mm:ss"}, \
{"name":"ticker_name", "type": "SYMBOL"} \
]' \
-F data=@trades.csv 'http://localhost:9000/imp'

For nanosecond-precision timestamps such as 2021-06-22T12:08:41.077338934Z, a pattern can be provided in the following way:

curl \
-F schema='[ \
{"name":"ts", "type": "TIMESTAMP", "pattern": "yyyy-MM-ddTHH:mm:ss.SSSUUUNNNZ"} \
]' \
-F data=@my_file.csv \
http://localhost:9000/imp

More information on the patterns for timestamps can be found on the date and time functions page.

note

The schema object must precede the data object in calls to this REST endpoint. For example:

# correct order
curl -F schema='{my_schema_obj}' -F data=@my_file.csv http://localhost:9000/imp
# incorrect order
curl -F data=@my_file.csv -F schema='{my_schema_obj}' http://localhost:9000/imp

Text loader configuration#

QuestDB uses a text_loader.json configuration file which can be placed in the server's conf directory. This file does not exist by default, but has the following implicit settings:

conf/text_loader.json
{
"date": [
{
"format": "dd/MM/y"
},
{
"format": "yyyy-MM-dd HH:mm:ss"
},
{
"format": "yyyy-MM-ddTHH:mm:ss.SSSz",
"locale": "en-US",
"utf8": false
},
{
"format": "MM/dd/y"
}
],
"timestamp": [
{
"format": "yyyy-MM-ddTHH:mm:ss.SSSUUUz",
"utf8": false
}
]
}

Example#

Given a CSV file which contains timestamps in the format yyyy-MM-dd - HH:mm:ss.SSSUUU, the following text loader configuration will provide the correct timestamp parsing:

conf/text_loader.json
{
"date": [
{
"format": "dd/MM/y"
},
{
"format": "yyyy-MM-dd HH:mm:ss"
},
{
"format": "yyyy-MM-ddTHH:mm:ss.SSSz",
"locale": "en-US",
"utf8": false
},
{
"format": "MM/dd/y"
}
],
"timestamp": [
{
"format": "yyyy-MM-ddTHH:mm:ss.SSSUUUz",
"utf8": false
},
{
"format": "yyyy-MM-dd - HH:mm:ss.SSSUUU",
"utf8": false
}
]
}

The CSV data can then be loaded via POST request, for example, using cURL:

curl -F data=@weather.csv 'http://localhost:9000/imp'

For more information on the /imp entry point, refer to the REST API documentation.