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import subprocess
from airflow.hooks.base_hook import BaseHook
from airflow.exceptions import AirflowException
[docs]class SparkSqlHook(BaseHook):
"""
This hook is a wrapper around the spark-sql binary. It requires that the
"spark-sql" binary is in the PATH.
:param sql: The SQL query to execute
:type sql: str
:param conf: arbitrary Spark configuration property
:type conf: str (format: PROP=VALUE)
:param conn_id: connection_id string
:type conn_id: str
:param total_executor_cores: (Standalone & Mesos only) Total cores for all executors
(Default: all the available cores on the worker)
:type total_executor_cores: int
:param executor_cores: (Standalone & YARN only) Number of cores per
executor (Default: 2)
:type executor_cores: int
:param executor_memory: Memory per executor (e.g. 1000M, 2G) (Default: 1G)
:type executor_memory: str
:param keytab: Full path to the file that contains the keytab
:type keytab: str
:param master: spark://host:port, mesos://host:port, yarn, or local
:type master: str
:param name: Name of the job.
:type name: str
:param num_executors: Number of executors to launch
:type num_executors: int
:param verbose: Whether to pass the verbose flag to spark-sql
:type verbose: bool
:param yarn_queue: The YARN queue to submit to (Default: "default")
:type yarn_queue: str
"""
def __init__(self,
sql,
conf=None,
conn_id='spark_sql_default',
total_executor_cores=None,
executor_cores=None,
executor_memory=None,
keytab=None,
principal=None,
master='yarn',
name='default-name',
num_executors=None,
verbose=True,
yarn_queue='default'
):
self._sql = sql
self._conf = conf
self._conn = self.get_connection(conn_id)
self._total_executor_cores = total_executor_cores
self._executor_cores = executor_cores
self._executor_memory = executor_memory
self._keytab = keytab
self._principal = principal
self._master = master
self._name = name
self._num_executors = num_executors
self._verbose = verbose
self._yarn_queue = yarn_queue
self._sp = None
def get_conn(self):
pass
def _prepare_command(self, cmd):
"""
Construct the spark-sql command to execute. Verbose output is enabled
as default.
:param cmd: command to append to the spark-sql command
:type cmd: str
:return: full command to be executed
"""
connection_cmd = ["spark-sql"]
if self._conf:
for conf_el in self._conf.split(","):
connection_cmd += ["--conf", conf_el]
if self._total_executor_cores:
connection_cmd += ["--total-executor-cores", str(self._total_executor_cores)]
if self._executor_cores:
connection_cmd += ["--executor-cores", str(self._executor_cores)]
if self._executor_memory:
connection_cmd += ["--executor-memory", self._executor_memory]
if self._keytab:
connection_cmd += ["--keytab", self._keytab]
if self._principal:
connection_cmd += ["--principal", self._principal]
if self._num_executors:
connection_cmd += ["--num-executors", str(self._num_executors)]
if self._sql:
sql = self._sql.strip()
if sql.endswith(".sql") or sql.endswith(".hql"):
connection_cmd += ["-f", sql]
else:
connection_cmd += ["-e", sql]
if self._master:
connection_cmd += ["--master", self._master]
if self._name:
connection_cmd += ["--name", self._name]
if self._verbose:
connection_cmd += ["--verbose"]
if self._yarn_queue:
connection_cmd += ["--queue", self._yarn_queue]
connection_cmd += cmd
self.log.debug("Spark-Sql cmd: %s", connection_cmd)
return connection_cmd
[docs] def run_query(self, cmd="", **kwargs):
"""
Remote Popen (actually execute the Spark-sql query)
:param cmd: command to remotely execute
:param kwargs: extra arguments to Popen (see subprocess.Popen)
"""
spark_sql_cmd = self._prepare_command(cmd)
self._sp = subprocess.Popen(spark_sql_cmd,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
**kwargs)
for line in iter(self._sp.stdout.readline, ''):
self.log.info(line)
returncode = self._sp.wait()
if returncode:
raise AirflowException(
"Cannot execute {} on {}. Process exit code: {}.".format(
cmd, self._conn.host, returncode
)
)
def kill(self):
if self._sp and self._sp.poll() is None:
self.log.info("Killing the Spark-Sql job")
self._sp.kill()