Create an interactive session. The following POST request starts a new Spark cluster with a remote Spark interpreter; the remote Spark interpreter is used to receive and execute code snippets, and return the result.

POST /sessions
        host = 'http://localhost:8998'
        data = {'kind': 'spark'}
        headers = {'Content-Type': 'application/json'}
        r = requests.post(host + '/sessions', data=json.dumps(data), headers=headers)
        r.json()

{u'state': u'starting', u'id': 0, u'kind': u'spark'}

Submit a statement. The following POST request submits a code snippet to a remote Spark interpreter, and returns a statement ID for querying the result after execution is finished.

POST /sessions/{sessionId}/statements
        data = {'code': 'sc.parallelize(1 to 10).count()'}
        r = requests.post(statements_url, data=json.dumps(data), headers=headers)
        r.json()

{u'output': None, u'state': u'running', u'id': 0}

Get the result of a statement. The following GET request returns the result of a statement in JSON format, which you can parse to extract elements of the result.

GET /sessions/{sessionId}/statements/{statementId}
        statement_url = host + r.headers['location']
        r = requests.get(statement_url, headers=headers)
        pprint.pprint(r.json())

{u'id': 0,
   u'output': {u'data': {u'text/plain': u'res0: Long = 10'},
               u'execution_count': 0,
               u'status': u'ok'},
   u'state': u'available'}