""" This is a script to submit dmlc job via Yarn dmlc will run as a Yarn application """ # pylint: disable=invalid-name, too-many-locals, too-many-branches, missing-docstring from __future__ import absolute_import import os import subprocess import warnings import logging import platform from threading import Thread from . import opts from . import tracker def yarn_submit(args, nworker, nserver, pass_env): """Submission function for YARN.""" is_windows = os.name == 'nt' hadoop_home = os.getenv('HADOOP_HOME') assert hadoop_home is not None, 'Need to set HADOOP_HOME for YARN submission.' hadoop_binary = os.path.join(hadoop_home, 'bin', 'hadoop') assert os.path.exists(hadoop_binary), "HADOOP_HOME does not contain the hadoop binary" if args.jobname is None: if args.num_servers == 0: prefix = ('DMLC[nworker=%d]:' % args.num_workers) else: prefix = ('DMLC[nworker=%d,nsever=%d]:' % (args.num_workers, args.num_servers)) args.jobname = prefix + args.command[0].split('/')[-1] # Determine path for Yarn helpers YARN_JAR_PATH = os.path.join(args.yarn_app_dir, 'dmlc-yarn.jar') curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__))) YARN_BOOT_PY = os.path.join(curr_path, 'launcher.py') if not os.path.exists(YARN_JAR_PATH): warnings.warn("cannot find \"%s\", I will try to run build" % YARN_JAR_PATH) cmd = 'cd %s;./build.%s' % \ (os.path.join(os.path.dirname(__file__), os.pardir, 'yarn'), 'bat' if is_windows else 'sh') print(cmd) subprocess.check_call(cmd, shell=True, env=os.environ) assert os.path.exists(YARN_JAR_PATH), "failed to build dmlc-yarn.jar, try it manually" # detech hadoop version (out, _) = subprocess.Popen('%s version' % hadoop_binary, shell=True, stdout=subprocess.PIPE).communicate() out = out.split('\n')[0].split() assert out[0] == 'Hadoop', 'cannot parse hadoop version string' hadoop_version = int(out[1].split('.')[0]) (classpath, _) = subprocess.Popen('%s classpath' % hadoop_binary, shell=True, stdout=subprocess.PIPE).communicate() classpath = classpath.strip() if hadoop_version < 2: raise RuntimeError('Hadoop Version is %s, dmlc_yarn will need Yarn(Hadoop 2.0)' % out[1]) fset, new_command = opts.get_cache_file_set(args) fset.add(YARN_JAR_PATH) fset.add(YARN_BOOT_PY) ar_list = [] for fname in args.archives: fset.add(fname) ar_list.append(os.path.basename(fname)) JAVA_HOME = os.getenv('JAVA_HOME') if JAVA_HOME is None: JAVA = 'java' else: JAVA = os.path.join(JAVA_HOME, 'bin', 'java') cmd = '%s -cp %s%s%s org.apache.hadoop.yarn.dmlc.Client '\ % (JAVA, classpath, ';' if is_windows else ':', YARN_JAR_PATH) env = os.environ.copy() for k, v in pass_env.items(): env[k] = str(v) # ship lib-stdc++.so if args.ship_libcxx is not None: if platform.architecture()[0] == '64bit': libcxx = args.ship_libcxx + '/libstdc++.so.6' else: libcxx = args.ship_libcxx + '/libstdc++.so' fset.add(libcxx) # update local LD_LIBRARY_PATH LD_LIBRARY_PATH = env['LD_LIBRARY_PATH'] if 'LD_LIBRARY_PATH' in env else '' env['LD_LIBRARY_PATH'] = args.ship_libcxx + ':' + LD_LIBRARY_PATH env['DMLC_JOB_CLUSTER'] = 'yarn' env['DMLC_WORKER_CORES'] = str(args.worker_cores) env['DMLC_WORKER_MEMORY_MB'] = str(args.worker_memory_mb) env['DMLC_SERVER_CORES'] = str(args.server_cores) env['DMLC_SERVER_MEMORY_MB'] = str(args.server_memory_mb) env['DMLC_NUM_WORKER'] = str(args.num_workers) env['DMLC_NUM_SERVER'] = str(args.num_servers) env['DMLC_JOB_ARCHIVES'] = ':'.join(ar_list) for f in fset: cmd += ' -file %s' % f cmd += ' -jobname %s ' % args.jobname cmd += ' -tempdir %s ' % args.hdfs_tempdir cmd += ' -queue %s ' % args.queue if args.yarn_app_classpath: cmd += ' -appcp %s ' % args.yarn_app_classpath for entry in args.env: cmd += ' -env %s ' % entry cmd += (' '.join(['./launcher.py'] + new_command)) logging.debug("Submit job with %d workers and %d servers", nworker, nserver) def run(): """internal running function.""" logging.debug(cmd) subprocess.check_call(cmd, shell=True, env=env) thread = Thread(target=run, args=()) thread.setDaemon(True) thread.start() return thread def submit(args): submit_thread = [] def yarn_submit_pass(nworker, nserver, pass_env): submit_thread.append(yarn_submit(args, nworker, nserver, pass_env)) curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__))) YARN_BOOT_PY = os.path.join(curr_path, 'launcher.py') tracker.submit(args.num_workers, args.num_servers, fun_submit=yarn_submit_pass, pscmd=(' '.join([YARN_BOOT_PY] + args.command)))