CartoDB-SQL-API/doc/copy_queries.md

Copy Queries

Copy queries allow you to use the PostgreSQL copy command for efficient streaming of data to and from CARTO.

The support for copy is split across two API end points:

• http://{username}.carto.com/api/v2/sql/copyfrom for uploading data to CARTO
• http://{username}.carto.com/api/v2/sql/copyto for exporting data out of CARTO

Copy From

The PostgreSQL COPY command is extremely fast, but requires very precise inputs:

• A COPY command that describes the table and columns of the upload file, and the format of the file.
• An upload file that exactly matches the COPY command.

If the COPY command, the supplied file, and the target table do not all match, the upload will fail.

"Copy from" copies data "from" your file, "to" CARTO. "Copy from" uses chunked encoding (Transfer-Encoding: chunked) to stream an upload file to the server. This avoids limitations around file size and any need for temporary storage: the data travels from your file straight into the database.

Parameter	Description
api_key	a write-enabled key
q	the COPY command to load the data

The actual COPY file content must be sent as the body of the POST request.

Composing a chunked POST is moderately complicated, so most developers will use a tool or scripting language to upload data to CARTO via "copy from".

Example

For a table to be readable by CARTO, it must have a minimum of three columns with specific data types:

• cartodb_id, a serial primary key
• the_geom, a geometry in the ESPG:4326 projection (aka long/lat)
• the_geom_webmercator, a geometry in the ESPG:3857 projection (aka web mercator)

Creating a new CARTO table with all the right triggers and columns can be tricky, so here is an example:

-- create the table using the *required* columns and a
-- couple more
CREATE TABLE upload_example (
    the_geom geometry,
    name text,
    age integer
);

-- adds the 'cartodb_id' and 'the_geom_webmercator'
-- adds the required triggers and indexes
SELECT CDB_CartodbfyTable('upload_example');

-- Note that CDB_CartodbfyTable is called differently if you have an organization user
-- SELECT CDB_CartodbfyTable('your_org_username', 'upload_example');

Now you are ready to upload your file. Suppose you have a CSV file like this:

the_geom,name,age
SRID=4326;POINT(-126 54),North West,89
SRID=4326;POINT(-96 34),South East,99
SRID=4326;POINT(-6 -25),Souther Easter,124

The COPY command to upload this file needs to specify the file format (CSV), the fact that there is a header line before the actual data begins, and to enumerate the columns that are in the file so they can be matched to the table columns.

COPY upload_example (the_geom, name, age)
FROM STDIN WITH (FORMAT csv, HEADER true)

The FROM STDIN option tells the database that the input will come from a data stream, and the SQL API will read our uploaded file and use it to feed the stream.

To actually run upload, you will need a tool or script that can generate a chunked POST, so here are a few examples in different languages.

CURL Example

The curl utility makes it easy to run web requests from the command-line, and supports chunked POST upload, so it can feed the copyfrom end point.

Assuming that you have already created the table, and that the CSV file is named "upload_example.csv":

curl -X POST \
    -H "Transfer-Encoding: chunked" \
    -H "Content-Type: application/octet-stream" \
    --data-binary @upload_example.csv \
    "http://{username}.carto.com/api/v2/sql/copyfrom?api_key={api_key}&q=COPY+upload_example+(the_geom,+name,+age)+FROM+STDIN+WITH+(FORMAT+csv,+HEADER+true)"

To upload a larger file, using compression for a faster transfer, first compress the file, and then upload it with the content encoding set:

curl -X POST  \
    -H "Content-Encoding: gzip" \
    -H "Transfer-Encoding: chunked" \
    -H "Content-Type: application/octet-stream" \
    --data-binary @upload_example.csv.gz \
    "http://{username}.carto.com/api/v2/sql/copyfrom?api_key={api_key}&q=COPY+upload_example+(the_geom,+name,+age)+FROM+STDIN+WITH+(FORMAT+csv,+HEADER+true)"

Python Example

The Requests library for HTTP makes doing a file upload relatively terse.

import requests

api_key = {api_key}
username = {api_key}
upload_file = 'upload_example.csv'
q = "COPY upload_example (the_geom, name, age) FROM STDIN WITH (FORMAT csv, HEADER true)"

url = "http://%s.carto.com/api/v2/sql/copyfrom" % username
with open(upload_file, 'rb') as f:
    r = requests.post(url, params={'api_key': api_key, 'q': q}, data=f, stream=True)

    if r.status_code != 200:
        print(r.text)
    else:
        status = r.json()
        print("Success: %s rows imported" % status['total_rows'])

A slightly more sophisticated script could read the headers from the CSV and compose the COPY command on the fly.

CSV files and column ordering

When using the CSV format, please note that PostgreSQL ignores the header.

HEADER

Specifies that the file contains a header line with the names of each column in the file. On output, the first line contains the column names from the table, and on input, the first line is ignored. This option is allowed only when using CSV format.

If the ordering of the columns does not match the table definition, you must specify it as part of the query.

For example, if your table is defined as:

CREATE TABLE upload_example (
    the_geom geometry,
    name text,
    age integer
);

but your CSV file has the following structure (note name and age columns are swapped):

#the_geom,age,name
SRID=4326;POINT(-126 54),89,North West
SRID=4326;POINT(-96 34),99,South East
SRID=4326;POINT(-6 -25),124,Souther Easter

your query has to specify the correct ordering, regardless of the header in the CSV:

COPY upload_example (the_geom, age, name) FROM stdin WITH (FORMAT csv, HEADER true);

Response Format

A successful upload will return with status code 200, and a small JSON with information about the upload.

{"time":0.046,"total_rows":10}

A failed upload will return with status code 400 and a larger JSON with the PostgreSQL error string, and a stack trace from the SQL API.

{"error":["Unexpected field"]}

Copy To

"Copy to" copies data "to" your desired output file, "from" CARTO.

Using the copyto end point to extract data bypasses the usual JSON formatting applied by the SQL API, so it can dump more data, faster. However, it has the restriction that it will only output in a handful of formats:

• PgSQL text format,
• CSV, and
• PgSQL binary format.

"Copy to" is a simple HTTP GET end point, so any tool or language can be easily used to download data, supplying the following parameters in the URL.

Parameter	Description
api_key	your API key for reading non-public tables
q	the COPY command to extract the data
filename	filename to put in the "Content-disposition" HTTP header, useful for tools that automatically save the download to a file name

CURL Example

The SQL to start a "copy to" can specify

• a table to read,
• a table and subset of columns to read, or
• an arbitrary SQL query to execute and read.

For our example, we'll read back just the three columns we originally loaded:

COPY upload_example (the_geom, name, age) TO stdout WITH (FORMAT csv, HEADER true)

The SQL needs to be URL-encoded before being embedded in the CURL command, so the final result looks like this:

curl \
    --output upload_example_dl.csv \
	--compressed \
    "http://{username}.carto.com/api/v2/sql/copyto?q=COPY+upload_example+(the_geom,name,age)+TO+stdout+WITH(FORMAT+csv,HEADER+true)&api_key={api_key}"

Python Example

The Python to "copy to" is very simple, because the HTTP call is a simple get. The only complexity in this example is at the end, where the result is streamed back block-by-block, to avoid pulling the entire download into memory before writing to file.

import requests

api_key = {api_key}
username = {api_key}
download_filename = 'download_example.csv'
q = "COPY upload_example (the_geom, name, age) TO stdout WITH (FORMAT csv, HEADER true)"

# request the download
url = "http://%s.carto.com/api/v2/sql/copyto" % username
r = requests.get(url, params={'api_key': api_key, 'q': q}, stream=True)
r.raise_for_status()

with open(download_filename, 'wb') as handle:
    for block in r.iter_content(1024):
        handle.write(block)
print("Downloaded to: %s" % savefilename)