Remote service input and output data formats¶
When Snowflake sends data to a remote service, or receives data from a remote service, the data must be formatted correctly. This topic provides information about the proper data formats. Data received from and returned to Snowflake must also be of an appropriate data type.
When executing an external function, for example, Snowflake sends and expects data in the format described here. It sends the data to a proxy service, not directly to the remote service (for more, see Introduction to external functions). Therefore, the proxy service must receive (and return) data in a Snowflake-compatible format. Although typically the proxy service passes data through unchanged, the proxy can reformat data (both sending and receiving) to meet the needs of both the remote service and Snowflake.
For simplicity, and to help illustrate the formats that Snowflake expects to send and receive, most of the examples in this section assume that the remote service reads and writes data in the same format as Snowflake expects, and the proxy service passes data through unchanged in both directions.
Data format sent by Snowflake¶
Each HTTP request from Snowflake is a POST or a GET.
A POST request contains headers and a request body. The request body includes a batch of rows.
A GET contains only headers, and is used only for polling when the remote service returns results asynchronously.
Body format¶
The body of the POST request contains the data, serialized in JSON format.
The schema for the JSON is:
The top-level is a JSON object (a set of name/value pairs, also called a “dictionary”).
Currently, there is exactly one item in that object; the key for that item is named “data”.
That “data” item’s value is a JSON array, in which:
Each element is one row of data.
Each row of data is a JSON array of one or more columns.
The first column is always the row number (i.e. the 0-based index of the row within the batch).
The remaining columns contain the arguments to the function.
Data types are serialized as follows:
Numbers are serialized as JSON numbers.
Booleans are serialized as JSON booleans.
Strings are serialized as JSON strings.
Objects are serialized as JSON objects.
All other supported data types are serialized as JSON strings.
Dates, times, and timestamps are serialized as strings. For details about formatting these data types as strings, see Date and time input and output formats and Date and time formats in conversion functions.
Binary columns are serialized as strings. For details, see Overview of supported binary formats.
NULL is serialized as JSON null.
For examples of extracting data in a remote service on each platform, see:
Optionally, the JSON can be compressed for transmission over the network. Compression is documented in CREATE EXTERNAL FUNCTION.
Body example¶
Here’s an example of a serialized request for an external function with the signature
f(integer, varchar, timestamp)
. Note that the first column is the row number within the batch, and the
next three values are the arguments to the external function.
{ "data": [ [0, 10, "Alex", "2014-01-01 16:00:00"], [1, 20, "Steve", "2015-01-01 16:00:00"], [2, 30, "Alice", "2016-01-01 16:00:00"], [3, 40, "Adrian", "2017-01-01 16:00:00"] ] }
Header format¶
The header information is generally available to the remote service as a set of key/value pairs. The header information includes:
The following HTTP headers:
Headers that describe how data is serialized in the request body:
“sf-external-function-format”: This is currently always set to “json”.
“sf-external-function-format-version”: This is currently always set to “1.0”.
“sf-external-function-current-query-id”: This contains the query ID of the query that called this external function. You can use this to correlate Snowflake queries to calls of the remote service, for example to help debug issues.
“sf-external-function-query-batch-id”: The batch ID uniquely identifies the specific batch of rows processed with this request. The remote service can use this ID to track the status of a batch that is being processed. The ID can also be used as an idempotency token if requests are retried due to an error. The ID can also be used for logging/tracing of requests by the remote service.
The batch ID in a GET is the same as the batch ID in the corresponding POST.
The batch ID is an opaque value generated by Snowflake. The format could change in future releases, so remote services should not rely on a specific format or try to interpret the value.
Headers that describe the signature (name and argument types) and return type of the external function that was called in the SQL query. These values can have characters that are not standard characters for Snowflake identifiers, so base64 versions of the information are included, and non-standard characters are replaced with a blank in the non-base64 versions.
The specific headers are:
sf-external-function-name
sf-external-function-name-base64
sf-external-function-signature
sf-external-function-signature-base64
sf-external-function-return-type
sf-external-function-return-type-base64
For example, the headers sent for the function
ext_func(n integer) returns varchar
are:sf-external-function-name: ext_func
sf-external-function-name-base64: <base64 value>
sf-external-function-signature: (N NUMBER)
sf-external-function-signature-base64: <base64 value>
sf-external-function-return-type: VARCHAR(16777216)
sf-external-function-return-type-base64: <base64 value>
Note that because SQL INTEGER values are treated as SQL NUMBER, the SQL argument declared as type
INTEGER
is described as typeNUMBER
.
Additional optional metadata described in the “headers” and “context_headers” properties of CREATE EXTERNAL FUNCTION.
Header access example¶
To extract the “sf-external-function-signature” header from inside an AWS Lambda function written in Python, which receives the headers as a Python dictionary, execute the following:
def handler(event, context): request_headers = event["headers"] signature = request_headers["sf-external-function-signature"]
The details will be different for other languages and on other cloud platforms.
For remote services developed on AWS, more information about headers and lambda proxy integration is available in the AWS API Gateway documentation .
Data format received by Snowflake¶
Body format¶
When a remote service finishes processing a batch, the remote service should send data back to Snowflake in a JSON format similar to the format of the data sent by Snowflake.
The JSON response returned to Snowflake should contain one row for each row sent by Snowflake. Each returned row contains two values:
The row number (i.e. the 0-based index of the row within the batch).
The value returned from the function for that row. The value can be a compound value (for example, an OBJECT), but it must be exactly one value because all scalar Snowflake functions (external or otherwise) return a single value.
So that Snowflake can correlate the response with the request, the row numbers in the returned data must correspond to the row numbers in the data that Snowflake sent and must be returned in the same order as they were received.
Body access example¶
The following JSON example shows two rows containing an OBJECT value, each preceded by a row number:
{
"data":
[
[ 0, { "City" : "Warsaw", "latitude" : 52.23, "longitude" : 21.01 } ],
[ 1, { "City" : "Toronto", "latitude" : 43.65, "longitude" : -79.38 } ]
]
}
To compose one of these returned rows with Python, you might use the following code:
...
row_number = 0
output_value = {}
output_value["city"] = "Warsaw"
output_value["latitude"] = 21.01
output_value["longitude"] = 52.23
row_to_return = [row_number, output_value]
...
To access the OBJECT value of a returned row with SQL, use the notation described in Traversing Semi-structured Data. For example:
select val:city, val:latitude, val:longitude
from (select ext_func_city_lat_long(city_name) as val from table_of_city_names);
Header format¶
The response can also contain the following optional HTTP headers:
Content-MD5: Snowflake uses the optional Content-MD5 header to check the integrity of the response. If this header is included in the response, Snowflake computes an MD5 checksum on the response body to ensure that it matches the corresponding checksum in the returned header. If the values do not match, the SQL query fails. The checksum should be encoded in a base64 representation before being returned in the header. See the example code below.
Optionally, the JSON can be compressed for transmission over the network. Compression is documented in CREATE EXTERNAL FUNCTION.
For information about timeouts and retries, see Account for timeout errors and Do not assume that the remote service is passed each row exactly once.
Status code¶
The response also contains an HTTP status code. Snowflake recognizes the following HTTP status codes:
Code |
Description |
---|---|
200 |
Batch processed successfully. |
202 |
Batch received and still being processed. |
Other values are treated as errors.
Response creation example¶
The example Python code below returns a proper response, including the HTTP response code, the processed data, and an MD5 header (which is optional).
This example is based on an AWS Lambda function. Some code might need customization for different platforms.
import json
import hashlib
import base64
def handler(event, context):
# The return value should contain an array of arrays (one inner array
# per input row for a scalar function).
array_of_rows_to_return = [ ]
...
json_compatible_string_to_return = json.dumps({"data" : array_of_rows_to_return})
# Calculate MD5 checksum for the response
md5digest = hashlib.md5(json_compatible_string_to_return.encode('utf-8')).digest()
response_headers = {
'Content-MD5' : base64.b64encode(md5digest)
}
# Return the HTTP status code, the processed data, and the headers
# (including the Content-MD5 header).
return {
'statusCode': 200,
'body': json_compatible_string_to_return,
'headers': response_headers
}