POST /v1/sql

Spice supports SQL queries directly from HTTP requests.

An example cURL:

curl -XPOST "127.0.0.1:8090/v1/sql" \
     --data "SELECT avg(total_amount), \
                    avg(tip_amount), \
                    count(1), \
                    passenger_count \
              FROM my_table \
              GROUP BY passenger_count \
              ORDER BY passenger_count ASC \
              LIMIT 3"

Response:

[
  {
    "AVG(my_table.tip_amount)": 3.072259971396793,
    "AVG(my_table.total_amount)": 25.327816939456525,
    "COUNT(Int64(1))": 31465,
    "passenger_count": 0
  },
  {
    "AVG(my_table.tip_amount)": 3.3712622884680057,
    "AVG(my_table.total_amount)": 26.205230445474996,
    "COUNT(Int64(1))": 2188739,
    "passenger_count": 1
  },
  {
    "AVG(my_table.tip_amount)": 3.7171302113290854,
    "AVG(my_table.total_amount)": 29.520659930930304,
    "COUNT(Int64(1))": 405103,
    "passenger_count": 2
  }
]

This allows for simple integration into any language or framework.

Python

from typing import Optional
import requests
import pandas as pd

def query_runtime(query: str, url: str =  "http://127.0.0.1:8090") -> Optional[pd.DataFrame]:
    response = requests.post(url, data=query)

    if response.status_code != 200:
        print(f"Error: Received status code {response.status_code}")
        return None

    return pd.DataFrame(response.json())

Javascript

async function queryRuntime(query, url = "http://127.0.0.1:8090") {
    try {
        const response = await fetch(url, {method: 'POST', body: query});
        if (!response.ok) {
        console.error(`Error: Received status code ${response.status}`);
        return null;
        }

        return await response.json();
    } catch (error) {
        return error;
    }
}