Source code for airflow.contrib.hooks.gcp_dataflow_hook

# -*- coding: utf-8 -*-
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import json
import re
import select
import subprocess
import time
import uuid

from googleapiclient.discovery import build

from airflow.contrib.hooks.gcp_api_base_hook import GoogleCloudBaseHook
from airflow.utils.log.logging_mixin import LoggingMixin

# This is the default location

[docs]class _DataflowJob(LoggingMixin): def __init__(self, dataflow, project_number, name, location, poll_sleep=10, job_id=None, num_retries=None): self._dataflow = dataflow self._project_number = project_number self._job_name = name self._job_location = location self._job_id = job_id self._num_retries = num_retries self._job = self._get_job() self._poll_sleep = poll_sleep
[docs] def _get_job_id_from_name(self): jobs = self._dataflow.projects().locations().jobs().list( projectId=self._project_number, location=self._job_location ).execute(num_retries=self._num_retries) for job in jobs['jobs']: if job['name'].lower() == self._job_name.lower(): self._job_id = job['id'] return job return None
[docs] def _get_job(self): if self._job_id: job = self._dataflow.projects().locations().jobs().get( projectId=self._project_number, location=self._job_location, jobId=self._job_id).execute(num_retries=self._num_retries) elif self._job_name: job = self._get_job_id_from_name() else: raise Exception('Missing both dataflow job ID and name.') if job and 'currentState' in job: 'Google Cloud DataFlow job %s is %s', job['name'], job['currentState'] ) elif job: 'Google Cloud DataFlow with job_id %s has name %s', self._job_id, job['name'] ) else: 'Google Cloud DataFlow job not available yet..' ) return job
[docs] def wait_for_done(self): while True: if self._job and 'currentState' in self._job: if 'JOB_STATE_DONE' == self._job['currentState']: return True elif 'JOB_STATE_RUNNING' == self._job['currentState'] and \ 'JOB_TYPE_STREAMING' == self._job['type']: return True elif 'JOB_STATE_FAILED' == self._job['currentState']: raise Exception("Google Cloud Dataflow job {} has failed.".format( self._job['name'])) elif 'JOB_STATE_CANCELLED' == self._job['currentState']: raise Exception("Google Cloud Dataflow job {} was cancelled.".format( self._job['name'])) elif 'JOB_STATE_RUNNING' == self._job['currentState']: time.sleep(self._poll_sleep) elif 'JOB_STATE_PENDING' == self._job['currentState']: time.sleep(15) else: self.log.debug(str(self._job)) raise Exception( "Google Cloud Dataflow job {} was unknown state: {}".format( self._job['name'], self._job['currentState'])) else: time.sleep(15) self._job = self._get_job()
[docs] def get(self): return self._job
[docs]class _Dataflow(LoggingMixin): def __init__(self, cmd):"Running command: %s", ' '.join(cmd)) self._proc = subprocess.Popen( cmd, shell=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE, close_fds=True)
[docs] def _line(self, fd): if fd == self._proc.stderr.fileno(): line = b''.join(self._proc.stderr.readlines()) if line: self.log.warning(line[:-1]) return line if fd == self._proc.stdout.fileno(): line = b''.join(self._proc.stdout.readlines()) if line:[:-1]) return line
[docs] def _extract_job(line): # Job id info: job_id_pattern = re.compile( br'.**/jobs/([a-z|0-9|A-Z|\-|\_]+).*') matched_job = or '') if matched_job: return
[docs] def wait_for_done(self): reads = [self._proc.stderr.fileno(), self._proc.stdout.fileno()]"Start waiting for DataFlow process to complete.") job_id = None # Make sure logs are processed regardless whether the subprocess is # terminated. process_ends = False while True: ret =, [], [], 5) if ret is not None: for fd in ret[0]: line = self._line(fd) if line: job_id = job_id or self._extract_job(line) else:"Waiting for DataFlow process to complete.") if process_ends: break if self._proc.poll() is not None: # Mark process completion but allows its outputs to be consumed. process_ends = True if self._proc.returncode != 0: raise Exception("DataFlow failed with return code {}".format( self._proc.returncode)) return job_id
[docs]class DataFlowHook(GoogleCloudBaseHook): def __init__(self, gcp_conn_id='google_cloud_default', delegate_to=None, poll_sleep=10): self.poll_sleep = poll_sleep super(DataFlowHook, self).__init__(gcp_conn_id, delegate_to)
[docs] def get_conn(self): """ Returns a Google Cloud Dataflow service object. """ http_authorized = self._authorize() return build( 'dataflow', 'v1b3', http=http_authorized, cache_discovery=False)
[docs] def _start_dataflow(self, variables, name, command_prefix, label_formatter): variables = self._set_variables(variables) cmd = command_prefix + self._build_cmd(variables, label_formatter) job_id = _Dataflow(cmd).wait_for_done() _DataflowJob(self.get_conn(), variables['project'], name, variables['region'], self.poll_sleep, job_id, self.num_retries).wait_for_done()
[docs] def _set_variables(variables): if variables['project'] is None: raise Exception('Project not specified') if 'region' not in variables.keys(): variables['region'] = DEFAULT_DATAFLOW_LOCATION return variables
[docs] def start_java_dataflow(self, job_name, variables, dataflow, job_class=None, append_job_name=True): name = self._build_dataflow_job_name(job_name, append_job_name) variables['jobName'] = name def label_formatter(labels_dict): return ['--labels={}'.format( json.dumps(labels_dict).replace(' ', ''))] command_prefix = (["java", "-cp", dataflow, job_class] if job_class else ["java", "-jar", dataflow]) self._start_dataflow(variables, name, command_prefix, label_formatter)
[docs] def start_template_dataflow(self, job_name, variables, parameters, dataflow_template, append_job_name=True): variables = self._set_variables(variables) name = self._build_dataflow_job_name(job_name, append_job_name) self._start_template_dataflow( name, variables, parameters, dataflow_template)
[docs] def start_python_dataflow(self, job_name, variables, dataflow, py_options, append_job_name=True): name = self._build_dataflow_job_name(job_name, append_job_name) variables['job_name'] = name def label_formatter(labels_dict): return ['--labels={}={}'.format(key, value) for key, value in labels_dict.items()] self._start_dataflow(variables, name, ["python2"] + py_options + [dataflow], label_formatter)
[docs] def _build_dataflow_job_name(job_name, append_job_name=True): base_job_name = str(job_name).replace('_', '-') if not re.match(r"^[a-z]([-a-z0-9]*[a-z0-9])?$", base_job_name): raise ValueError( 'Invalid job_name ({}); the name must consist of' 'only the characters [-a-z0-9], starting with a ' 'letter and ending with a letter or number '.format(base_job_name)) if append_job_name: safe_job_name = base_job_name + "-" + str(uuid.uuid4())[:8] else: safe_job_name = base_job_name return safe_job_name
[docs] def _build_cmd(variables, label_formatter): command = ["--runner=DataflowRunner"] if variables is not None: for attr, value in variables.items(): if attr == 'labels': command += label_formatter(value) elif value is None or value.__len__() < 1: command.append("--" + attr) else: command.append("--" + attr + "=" + value) return command
[docs] def _start_template_dataflow(self, name, variables, parameters, dataflow_template): # Builds RuntimeEnvironment from variables dictionary # environment = {} for key in ['numWorkers', 'maxWorkers', 'zone', 'serviceAccountEmail', 'tempLocation', 'bypassTempDirValidation', 'machineType', 'additionalExperiments', 'network', 'subnetwork', 'additionalUserLabels']: if key in variables: environment.update({key: variables[key]}) body = {"jobName": name, "parameters": parameters, "environment": environment} service = self.get_conn() request = service.projects().locations().templates().launch( projectId=variables['project'], location=variables['region'], gcsPath=dataflow_template, body=body ) response = request.execute(num_retries=self.num_retries) variables = self._set_variables(variables) _DataflowJob(self.get_conn(), variables['project'], name, variables['region'], self.poll_sleep, num_retries=self.num_retries).wait_for_done() return response

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