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spark_ec2.py
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spark_ec2.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from __future__ import division, print_function, with_statement
import codecs
import hashlib
import itertools
import logging
import os
import os.path
import pipes
import random
import shutil
import string
from stat import S_IRUSR
import subprocess
import sys
import tarfile
import tempfile
import textwrap
import time
import warnings
from datetime import datetime
from optparse import OptionParser
from sys import stderr
if sys.version < "3":
from urllib2 import urlopen, Request, HTTPError
else:
from urllib.request import urlopen, Request
from urllib.error import HTTPError
raw_input = input
xrange = range
SPARK_EC2_VERSION = "2.1.1"
SPARK_EC2_DIR = os.path.dirname(os.path.realpath(__file__))
VALID_SPARK_VERSIONS = set([
"0.7.3",
"0.8.0",
"0.8.1",
"0.9.0",
"0.9.1",
"0.9.2",
"1.0.0",
"1.0.1",
"1.0.2",
"1.1.0",
"1.1.1",
"1.2.0",
"1.2.1",
"1.3.0",
"1.3.1",
"1.4.0",
"1.4.1",
"1.5.0",
"1.5.1",
"1.5.2",
"1.6.0",
"1.6.1",
"1.6.2",
"1.6.3",
"2.0.0-preview",
"2.0.0",
"2.0.1",
"2.0.2",
"2.1.0",
"2.1.1",
"2.2.0",
"2.2.1",
"2.3.0",
"2.3.1",
"2.3.2",
"2.4.0",
"2.4.1",
"2.4.2",
"2.4.3",
"2.4.4",
"2.4.5",
"2.4.6",
"2.4.7",
"3.0.0",
"3.0.1",
"3.0.2",
"3.1.1",
"3.2.0",
"3.2.1",
"3.2.2",
"3.2.3",
"3.3.0",
"3.3.1",
"3.3.2",
"3.3.3",
"3.4.0",
"3.4.1",
"3.5.0"
])
SPARK_TACHYON_MAP = {
"1.0.0": "0.4.1",
"1.0.1": "0.4.1",
"1.0.2": "0.4.1",
"1.1.0": "0.5.0",
"1.1.1": "0.5.0",
"1.2.0": "0.5.0",
"1.2.1": "0.5.0",
"1.3.0": "0.5.0",
"1.3.1": "0.5.0",
"1.4.0": "0.6.4",
"1.4.1": "0.6.4",
"1.5.0": "0.7.1",
"1.5.1": "0.7.1",
"1.5.2": "0.7.1",
"1.6.0": "0.8.2",
"1.6.1": "0.8.2",
"1.6.2": "0.8.2",
"2.0.0-preview": ""
}
DEFAULT_SPARK_VERSION = SPARK_EC2_VERSION
DEFAULT_SPARK_GITHUB_REPO = "https://github.com/apache/spark"
# Default location to get the spark-ec2 scripts (and ami-list) from
DEFAULT_SPARK_EC2_GITHUB_REPO = "https://github.com/amplab/spark-ec2"
DEFAULT_SPARK_EC2_BRANCH = "branch-2.0"
def setup_external_libs(libs):
"""
Download external libraries from PyPI to SPARK_EC2_DIR/lib/ and prepend them to our PATH.
"""
PYPI_URL_PREFIX = "https://pypi.python.org/packages/source"
SPARK_EC2_LIB_DIR = os.path.join(SPARK_EC2_DIR, "lib")
if not os.path.exists(SPARK_EC2_LIB_DIR):
print("Downloading external libraries that spark-ec2 needs from PyPI to {path}...".format(
path=SPARK_EC2_LIB_DIR
))
print("This should be a one-time operation.")
os.mkdir(SPARK_EC2_LIB_DIR)
for lib in libs:
versioned_lib_name = "{n}-{v}".format(n=lib["name"], v=lib["version"])
lib_dir = os.path.join(SPARK_EC2_LIB_DIR, versioned_lib_name)
if not os.path.isdir(lib_dir):
tgz_file_path = os.path.join(SPARK_EC2_LIB_DIR, versioned_lib_name + ".tar.gz")
print(" - Downloading {lib}...".format(lib=lib["name"]))
lib_url = lib.get("url",
"{prefix}/{first_letter}/{lib_name}/{lib_name}-{lib_version}.tar.gz".format(
prefix=PYPI_URL_PREFIX,
first_letter=lib["name"][:1],
lib_name=lib["name"],
lib_version=lib["version"])
)
print(lib_url)
download_stream = urlopen(lib_url)
with open(tgz_file_path, "wb") as tgz_file:
tgz_file.write(download_stream.read())
with open(tgz_file_path, "rb") as tar:
if hashlib.md5(tar.read()).hexdigest() != lib["md5"]:
print("ERROR: Got wrong md5sum for {lib}.".format(lib=lib["name"]), file=stderr)
sys.exit(1)
tar = tarfile.open(tgz_file_path)
tar.extractall(path=SPARK_EC2_LIB_DIR)
tar.close()
os.remove(tgz_file_path)
print(" - Finished downloading {lib}.".format(lib=lib["name"]))
sys.path.insert(1, lib_dir)
# Only PyPI libraries are supported.
external_libs = [
{
"name": "boto",
"version": "2.47.0",
"url": "https://pypi.python.org/packages/bc/ee/e674c01b10972765511705dc77b824b550646a30994cbc428087c4910ac3/boto-2.47.0.tar.gz#md5=c7ed986a6f369fe93f04ec62d16299ac",
"md5": "c7ed986a6f369fe93f04ec62d16299ac"
}
]
setup_external_libs(external_libs)
import boto
from boto.ec2.blockdevicemapping import BlockDeviceMapping, BlockDeviceType, EBSBlockDeviceType
from boto import ec2
class UsageError(Exception):
pass
# Configure and parse our command-line arguments
def parse_args():
parser = OptionParser(
prog="spark-ec2",
version="%prog {v}".format(v=SPARK_EC2_VERSION),
usage="%prog [options] <action> <cluster_name>\n\n"
+ "<action> can be: launch, destroy, login, stop, start, get-master, reboot-slaves")
parser.add_option(
"-s", "--slaves", type="int", default=1,
help="Number of slaves to launch (default: %default)")
parser.add_option(
"-w", "--wait", type="int",
help="DEPRECATED (no longer necessary) - Seconds to wait for nodes to start")
parser.add_option(
"-k", "--key-pair",
help="Key pair to use on instances")
parser.add_option(
"-i", "--identity-file",
help="SSH private key file to use for logging into instances")
parser.add_option(
"-p", "--profile", default=None,
help="If you have multiple profiles (AWS or boto config), you can configure " +
"additional, named profiles by using this option (default: %default)")
parser.add_option(
"-t", "--instance-type", default="m1.large",
help="Type of instance to launch (default: %default). " +
"WARNING: must be 64-bit; small instances won't work")
parser.add_option(
"-m", "--master-instance-type", default="",
help="Master instance type (leave empty for same as instance-type)")
parser.add_option(
"-r", "--region", default="us-east-1",
help="EC2 region used to launch instances in, or to find them in (default: %default)")
parser.add_option(
"-z", "--zone", default="",
help="Availability zone to launch instances in, or 'all' to spread " +
"slaves across multiple (an additional $0.01/Gb for bandwidth" +
"between zones applies) (default: a single zone chosen at random)")
parser.add_option(
"-a", "--ami",
help="Amazon Machine Image ID to use")
parser.add_option(
"-v", "--spark-version", default=DEFAULT_SPARK_VERSION,
help="Version of Spark to use: 'X.Y.Z' or a specific git hash (default: %default)")
parser.add_option(
"--spark-git-repo",
default=DEFAULT_SPARK_GITHUB_REPO,
help="Github repo from which to checkout supplied commit hash (default: %default)")
parser.add_option(
"--spark-ec2-git-repo",
default=DEFAULT_SPARK_EC2_GITHUB_REPO,
help="Github repo from which to checkout spark-ec2 (default: %default)")
parser.add_option(
"--spark-ec2-git-branch",
default=DEFAULT_SPARK_EC2_BRANCH,
help="Github repo branch of spark-ec2 to use (default: %default)")
parser.add_option(
"--deploy-root-dir",
default=None,
help="A directory to copy into / on the first master. " +
"Must be absolute. Note that a trailing slash is handled as per rsync: " +
"If you omit it, the last directory of the --deploy-root-dir path will be created " +
"in / before copying its contents. If you append the trailing slash, " +
"the directory is not created and its contents are copied directly into /. " +
"(default: %default).")
parser.add_option(
"--hadoop-major-version", default="yarn",
help="Major version of Hadoop. Valid options are 1 (Hadoop 1.0.4), 2 (CDH 4.2.0), yarn " +
"(Hadoop 2.4.0) (default: %default)")
parser.add_option(
"-D", metavar="[ADDRESS:]PORT", dest="proxy_port",
help="Use SSH dynamic port forwarding to create a SOCKS proxy at " +
"the given local address (for use with login)")
parser.add_option(
"--resume", action="store_true", default=False,
help="Resume installation on a previously launched cluster " +
"(for debugging)")
parser.add_option(
"--ebs-vol-size", metavar="SIZE", type="int", default=200,
help="Size (in GB) of each EBS volume.")
parser.add_option(
"--ebs-vol-type", default="gp2",
help="EBS volume type (e.g. 'gp2', 'standard').")
parser.add_option(
"--ebs-vol-num", type="int", default=1,
help="Number of EBS volumes to attach to each node as /vol[x]. " +
"The volumes will be deleted when the instances terminate. " +
"Only possible on EBS-backed AMIs. " +
"EBS volumes are only attached if --ebs-vol-size > 0. " +
"Only support up to 8 EBS volumes.")
parser.add_option(
"--placement-group", type="string", default=None,
help="Which placement group to try and launch " +
"instances into. Assumes placement group is already " +
"created.")
parser.add_option(
"--swap", metavar="SWAP", type="int", default=1024,
help="Swap space to set up per node, in MB (default: %default)")
parser.add_option(
"--spot-price", metavar="PRICE", type="float",
help="If specified, launch slaves as spot instances with the given " +
"maximum price (in dollars)")
parser.add_option(
"--ganglia", action="store_true", default=True,
help="Setup Ganglia monitoring on cluster (default: %default). NOTE: " +
"the Ganglia page will be publicly accessible")
parser.add_option(
"--no-ganglia", action="store_false", dest="ganglia",
help="Disable Ganglia monitoring for the cluster")
parser.add_option(
"-u", "--user", default="root",
help="The SSH user you want to connect as (default: %default)")
parser.add_option(
"--delete-groups", action="store_true", default=False,
help="When destroying a cluster, delete the security groups that were created")
parser.add_option(
"--use-existing-master", action="store_true", default=False,
help="Launch fresh slaves, but use an existing stopped master if possible")
parser.add_option(
"--worker-instances", type="int", default=1,
help="Number of instances per worker: variable SPARK_WORKER_INSTANCES. Not used if YARN " +
"is used as Hadoop major version (default: %default)")
parser.add_option(
"--master-opts", type="string", default="",
help="Extra options to give to master through SPARK_MASTER_OPTS variable " +
"(e.g -Dspark.worker.timeout=180)")
parser.add_option(
"--user-data", type="string", default="",
help="Path to a user-data file (most AMIs interpret this as an initialization script)")
parser.add_option(
"--authorized-address", type="string", default="0.0.0.0/0",
help="Address to authorize on created security groups (default: %default)")
parser.add_option(
"--additional-security-group", type="string", default="",
help="Additional security group to place the machines in")
parser.add_option(
"--additional-tags", type="string", default="",
help="Additional tags to set on the machines; tags are comma-separated, while name and " +
"value are colon separated; ex: \"Task:MySparkProject,Env:production\"")
parser.add_option(
"--tag-volumes", action="store_true", default=False,
help="Apply the tags given in --additional-tags to any EBS volumes " +
"attached to master and slave instances.")
parser.add_option(
"--copy-aws-credentials", action="store_true", default=False,
help="Add AWS credentials to hadoop configuration to allow Spark to access S3")
parser.add_option(
"--subnet-id", default=None,
help="VPC subnet to launch instances in")
parser.add_option(
"--vpc-id", default=None,
help="VPC to launch instances in")
parser.add_option(
"--private-ips", action="store_true", default=False,
help="Use private IPs for instances rather than public if VPC/subnet " +
"requires that.")
parser.add_option(
"--instance-initiated-shutdown-behavior", default="stop",
choices=["stop", "terminate"],
help="Whether instances should terminate when shut down or just stop")
parser.add_option(
"--instance-profile-name", default=None,
help="IAM profile name to launch instances under")
(opts, args) = parser.parse_args()
if len(args) != 2:
parser.print_help()
sys.exit(1)
(action, cluster_name) = args
# Boto config check
# http://boto.cloudhackers.com/en/latest/boto_config_tut.html
home_dir = os.getenv('HOME')
if home_dir is None or not os.path.isfile(home_dir + '/.boto'):
if not os.path.isfile('/etc/boto.cfg'):
# If there is no boto config, check aws credentials
if not os.path.isfile(home_dir + '/.aws/credentials'):
if os.getenv('AWS_ACCESS_KEY_ID') is None:
print("ERROR: The environment variable AWS_ACCESS_KEY_ID must be set",
file=stderr)
sys.exit(1)
if os.getenv('AWS_SECRET_ACCESS_KEY') is None:
print("ERROR: The environment variable AWS_SECRET_ACCESS_KEY must be set",
file=stderr)
sys.exit(1)
return (opts, action, cluster_name)
# Get the EC2 security group of the given name, creating it if it doesn't exist
def get_or_make_group(conn, name, vpc_id):
groups = conn.get_all_security_groups()
group = [g for g in groups if g.name == name]
if len(group) > 0:
return group[0]
else:
print("Creating security group " + name)
return conn.create_security_group(name, "Spark EC2 group", vpc_id)
def validate_spark_hadoop_version(spark_version, hadoop_version):
if "." in spark_version:
parts = spark_version.split(".")
if parts[0].isdigit():
spark_major_version = float(parts[0])
if spark_major_version > 1.0 and hadoop_version != "yarn":
print("Spark version: {v}, does not support Hadoop version: {hv}".
format(v=spark_version, hv=hadoop_version), file=stderr)
sys.exit(1)
else:
print("Invalid Spark version: {v}".format(v=spark_version), file=stderr)
sys.exit(1)
def get_validate_spark_version(version, repo):
if "." in version:
# Remove leading v to handle inputs like v1.5.0
version = version.lstrip("v")
if version not in VALID_SPARK_VERSIONS:
print("Don't know about Spark version: {v}".format(v=version), file=stderr)
sys.exit(1)
return version
else:
github_commit_url = "{repo}/commit/{commit_hash}".format(repo=repo, commit_hash=version)
request = Request(github_commit_url)
request.get_method = lambda: 'HEAD'
try:
response = urlopen(request)
except HTTPError as e:
print("Couldn't validate Spark commit: {url}".format(url=github_commit_url),
file=stderr)
print("Received HTTP response code of {code}.".format(code=e.code), file=stderr)
sys.exit(1)
return version
# Source: http://aws.amazon.com/amazon-linux-ami/instance-type-matrix/
# Last Updated: 2015-06-19
# For easy maintainability, please keep this manually-inputted dictionary sorted by key.
EC2_INSTANCE_TYPES = {
"c1.medium": "pvm",
"c1.xlarge": "pvm",
"c3.large": "hvm",
"c3.xlarge": "hvm",
"c3.2xlarge": "hvm",
"c3.4xlarge": "hvm",
"c3.8xlarge": "hvm",
"c4.large": "hvm",
"c4.xlarge": "hvm",
"c4.2xlarge": "hvm",
"c4.4xlarge": "hvm",
"c4.8xlarge": "hvm",
"cc1.4xlarge": "hvm",
"cc2.8xlarge": "hvm",
"cg1.4xlarge": "hvm",
"cr1.8xlarge": "hvm",
"d2.xlarge": "hvm",
"d2.2xlarge": "hvm",
"d2.4xlarge": "hvm",
"d2.8xlarge": "hvm",
"g2.2xlarge": "hvm",
"g2.8xlarge": "hvm",
"hi1.4xlarge": "pvm",
"hs1.8xlarge": "pvm",
"i2.xlarge": "hvm",
"i2.2xlarge": "hvm",
"i2.4xlarge": "hvm",
"i2.8xlarge": "hvm",
"m1.small": "pvm",
"m1.medium": "pvm",
"m1.large": "pvm",
"m1.xlarge": "pvm",
"m2.xlarge": "pvm",
"m2.2xlarge": "pvm",
"m2.4xlarge": "pvm",
"m3.medium": "hvm",
"m3.large": "hvm",
"m3.xlarge": "hvm",
"m3.2xlarge": "hvm",
"m4.large": "hvm",
"m4.xlarge": "hvm",
"m4.2xlarge": "hvm",
"m4.4xlarge": "hvm",
"m4.10xlarge": "hvm",
"r3.large": "hvm",
"r3.xlarge": "hvm",
"r3.2xlarge": "hvm",
"r3.4xlarge": "hvm",
"r3.8xlarge": "hvm",
"r4.large": "hvm",
"r4.xlarge": "hvm",
"r4.2xlarge": "hvm",
"r4.4xlarge": "hvm",
"r4.8xlarge": "hvm",
"r4.16xlarge": "hvm",
"r5.large": "hvm",
"r5.xlarge": "hvm",
"r5.2xlarge": "hvm",
"r5.4xlarge": "hvm",
"r5.8xlarge": "hvm",
"r5.12xlarge": "hvm",
"r5.24xlarge": "hvm",
"r5a.large": "hvm",
"r5a.xlarge": "hvm",
"r5a.2xlarge": "hvm",
"r5a.4xlarge": "hvm",
"r5a.12xlarge": "hvm",
"r5a.24xlarge": "hvm",
"t1.micro": "pvm",
"t2.micro": "hvm",
"t2.small": "hvm",
"t2.medium": "hvm",
"t2.large": "hvm",
"t3.large": "hvm",
"t3.xlarge": "hvm",
"t3.2xlarge": "hvm",
"x1.16xlarge": "hvm",
"x1.32xlarge": "hvm"
}
def get_tachyon_version(spark_version):
return SPARK_TACHYON_MAP.get(spark_version, "")
# Attempt to resolve an appropriate AMI given the architecture and region of the request.
def get_spark_ami(opts):
if opts.instance_type in EC2_INSTANCE_TYPES:
instance_type = EC2_INSTANCE_TYPES[opts.instance_type]
else:
instance_type = "pvm"
print("Don't recognize %s, assuming type is pvm" % opts.instance_type, file=stderr)
# URL prefix from which to fetch AMI information
ami_prefix = "{r}/{b}/ami-list".format(
r=opts.spark_ec2_git_repo.replace("https://github.com", "https://raw.github.com", 1),
b=opts.spark_ec2_git_branch)
ami_path = "%s/%s/%s" % (ami_prefix, opts.region, instance_type)
reader = codecs.getreader("ascii")
try:
ami = reader(urlopen(ami_path)).read().strip()
except:
print("Could not resolve AMI at: " + ami_path, file=stderr)
sys.exit(1)
print("Spark AMI: " + ami)
return ami
# Launch a cluster of the given name, by setting up its security groups,
# and then starting new instances in them.
# Returns a tuple of EC2 reservation objects for the master and slaves
# Fails if there already instances running in the cluster's groups.
def launch_cluster(conn, opts, cluster_name):
if opts.identity_file is None:
print("ERROR: Must provide an identity file (-i) for ssh connections.", file=stderr)
sys.exit(1)
if opts.key_pair is None:
print("ERROR: Must provide a key pair name (-k) to use on instances.", file=stderr)
sys.exit(1)
user_data_content = None
if opts.user_data:
with open(opts.user_data) as user_data_file:
user_data_content = user_data_file.read()
print("Setting up security groups... customized")
master_group = get_or_make_group(conn, cluster_name + "-master", opts.vpc_id)
slave_group = get_or_make_group(conn, cluster_name + "-slaves", opts.vpc_id)
authorized_address = opts.authorized_address
ssh_strict_group_name = 'ssh-strict-sg';
ssh_strict_group = get_or_make_group(conn, ssh_strict_group_name, opts.vpc_id)
if master_group.rules == []: # Group was just now created
if opts.vpc_id is None:
master_group.authorize(src_group=master_group)
master_group.authorize(src_group=slave_group)
else:
# master_group.authorize(ip_protocol='icmp', from_port=-1, to_port=-1,
# src_group=master_group)
master_group.authorize(ip_protocol='tcp', from_port=0, to_port=65535, src_group=master_group)
# master_group.authorize(ip_protocol='udp', from_port=0, to_port=65535,
# src_group=master_group)
# master_group.authorize(ip_protocol='icmp', from_port=-1, to_port=-1,
# src_group=slave_group)
master_group.authorize(ip_protocol='tcp', from_port=0, to_port=65535, src_group=slave_group)
# master_group.authorize(ip_protocol='udp', from_port=0, to_port=65535,
# src_group=slave_group)
master_group.authorize('tcp', 8080, 8081, authorized_address) # spark master,worker ui
master_group.authorize('tcp', 18080, 18080, authorized_address) # spark history ui
# master_group.authorize('tcp', 19999, 19999, authorized_address) # tachyon
# master_group.authorize('tcp', 50030, 50030, authorized_address) # mapred jobtracker
# master_group.authorize('tcp', 50070, 50070, authorized_address) # hdfs / dfs health
# master_group.authorize('tcp', 60070, 60070, authorized_address) # ???
master_group.authorize('tcp', 4040, 4045, authorized_address) # ??? spark running job/application ui
## Rstudio (GUI for R) needs port 8787 for web access
# master_group.authorize('tcp', 8787, 8787, authorized_address)
## HDFS NFS gateway requires 111,2049,4242 for tcp & udp
# master_group.authorize('tcp', 111, 111, authorized_address)
# master_group.authorize('udp', 111, 111, authorized_address)
# master_group.authorize('tcp', 2049, 2049, authorized_address)
# master_group.authorize('udp', 2049, 2049, authorized_address)
# master_group.authorize('tcp', 4242, 4242, authorized_address)
# master_group.authorize('udp', 4242, 4242, authorized_address)
# RM in YARN mode uses 8088
# master_group.authorize('tcp', 8088, 8088, authorized_address) # hadoop cluster ui
# if opts.ganglia:
# master_group.authorize('tcp', 5080, 5080, authorized_address)
if slave_group.rules == []: # Group was just now created
if opts.vpc_id is None:
slave_group.authorize(src_group=master_group)
slave_group.authorize(src_group=slave_group)
else:
# slave_group.authorize(ip_protocol='icmp', from_port=-1, to_port=-1,
# src_group=master_group)
slave_group.authorize(ip_protocol='tcp', from_port=0, to_port=65535, src_group=master_group)
# slave_group.authorize(ip_protocol='udp', from_port=0, to_port=65535,
# src_group=master_group)
# slave_group.authorize(ip_protocol='icmp', from_port=-1, to_port=-1,
# src_group=slave_group)
slave_group.authorize(ip_protocol='tcp', from_port=0, to_port=65535, src_group=slave_group)
# slave_group.authorize(ip_protocol='udp', from_port=0, to_port=65535,
# src_group=slave_group)
# slave_group.authorize('tcp', 8080, 8081, authorized_address)
# slave_group.authorize('tcp', 50060, 50060, authorized_address)
# slave_group.authorize('tcp', 50075, 50075, authorized_address)
# slave_group.authorize('tcp', 60060, 60060, authorized_address)
# slave_group.authorize('tcp', 60075, 60075, authorized_address)
# Check if instances are already running in our groups
existing_masters, existing_slaves = get_existing_cluster(conn, opts, cluster_name,
die_on_error=False)
if existing_slaves or (existing_masters and not opts.use_existing_master):
print("ERROR: There are already instances running in group %s or %s" %
(master_group.name, slave_group.name), file=stderr)
sys.exit(1)
# Figure out Spark AMI
if opts.ami is None:
opts.ami = get_spark_ami(opts)
# we use group ids to work around https://github.com/boto/boto/issues/350
additional_group_ids = []
if opts.additional_security_group:
additional_group_ids = [sg.id
for sg in conn.get_all_security_groups()
if opts.additional_security_group in (sg.name, sg.id)]
# our custom security group
print("Adding custom security group...")
additional_group_ids.append(ssh_strict_group.id)
print("Launching instances...")
try:
image = conn.get_all_images(image_ids=[opts.ami])[0]
except:
print("Could not find AMI " + opts.ami, file=stderr)
sys.exit(1)
# Create block device mapping so that we can add EBS volumes if asked to.
# The first drive is attached as /dev/sds, 2nd as /dev/sdt, ... /dev/sdz
block_map = BlockDeviceMapping()
if opts.ebs_vol_size > 0:
for i in range(opts.ebs_vol_num):
device = EBSBlockDeviceType()
device.size = opts.ebs_vol_size
device.volume_type = opts.ebs_vol_type
device.delete_on_termination = True
block_map["/dev/sd" + chr(ord('s') + i)] = device
# AWS ignores the AMI-specified block device mapping for M3 (see SPARK-3342).
if opts.instance_type.startswith('m3.'):
for i in range(get_num_disks(opts.instance_type)):
dev = BlockDeviceType()
dev.ephemeral_name = 'ephemeral%d' % i
# The first ephemeral drive is /dev/sdb.
name = '/dev/sd' + string.ascii_letters[i + 1]
block_map[name] = dev
# Launch slaves
if opts.spot_price is not None:
# Launch spot instances with the requested price
print("Requesting %d slaves as spot instances with price $%.3f" %
(opts.slaves, opts.spot_price))
zones = get_zones(conn, opts)
num_zones = len(zones)
i = 0
my_req_ids = []
for zone in zones:
num_slaves_this_zone = get_partition(opts.slaves, num_zones, i)
slave_reqs = conn.request_spot_instances(
price=opts.spot_price,
image_id=opts.ami,
launch_group="launch-group-%s" % cluster_name,
placement=zone,
count=num_slaves_this_zone,
key_name=opts.key_pair,
security_group_ids=[slave_group.id] + additional_group_ids,
instance_type=opts.instance_type,
block_device_map=block_map,
subnet_id=opts.subnet_id,
placement_group=opts.placement_group,
user_data=user_data_content,
instance_profile_name=opts.instance_profile_name)
my_req_ids += [req.id for req in slave_reqs]
i += 1
print("Waiting for spot instances to be granted...")
try:
while True:
time.sleep(10)
reqs = conn.get_all_spot_instance_requests()
id_to_req = {}
for r in reqs:
id_to_req[r.id] = r
active_instance_ids = []
for i in my_req_ids:
if i in id_to_req and id_to_req[i].state == "active":
active_instance_ids.append(id_to_req[i].instance_id)
if len(active_instance_ids) == opts.slaves:
print("All %d slaves granted" % opts.slaves)
reservations = conn.get_all_reservations(active_instance_ids)
slave_nodes = []
for r in reservations:
slave_nodes += r.instances
break
else:
print("%d of %d slaves granted, waiting longer" % (
len(active_instance_ids), opts.slaves))
except:
print("Canceling spot instance requests")
conn.cancel_spot_instance_requests(my_req_ids)
# Log a warning if any of these requests actually launched instances:
(master_nodes, slave_nodes) = get_existing_cluster(
conn, opts, cluster_name, die_on_error=False)
running = len(master_nodes) + len(slave_nodes)
if running:
print(("WARNING: %d instances are still running" % running), file=stderr)
sys.exit(0)
else:
# Launch non-spot instances
zones = get_zones(conn, opts)
num_zones = len(zones)
i = 0
slave_nodes = []
for zone in zones:
num_slaves_this_zone = get_partition(opts.slaves, num_zones, i)
if num_slaves_this_zone > 0:
slave_res = image.run(
key_name=opts.key_pair,
security_group_ids=[slave_group.id] + additional_group_ids,
instance_type=opts.instance_type,
placement=zone,
min_count=num_slaves_this_zone,
max_count=num_slaves_this_zone,
block_device_map=block_map,
subnet_id=opts.subnet_id,
placement_group=opts.placement_group,
user_data=user_data_content,
instance_initiated_shutdown_behavior=opts.instance_initiated_shutdown_behavior,
instance_profile_name=opts.instance_profile_name)
slave_nodes += slave_res.instances
print("Launched {s} slave{plural_s} in {z}, regid = {r}".format(
s=num_slaves_this_zone,
plural_s=('' if num_slaves_this_zone == 1 else 's'),
z=zone,
r=slave_res.id))
i += 1
# Launch or resume masters
if existing_masters:
print("Starting master...")
for inst in existing_masters:
if inst.state not in ["shutting-down", "terminated"]:
inst.start()
master_nodes = existing_masters
else:
master_type = opts.master_instance_type
if master_type == "":
master_type = opts.instance_type
if opts.zone == 'all':
opts.zone = random.choice(conn.get_all_zones()).name
master_res = image.run(
key_name=opts.key_pair,
security_group_ids=[master_group.id] + additional_group_ids,
instance_type=master_type,
placement=opts.zone,
min_count=1,
max_count=1,
block_device_map=block_map,
subnet_id=opts.subnet_id,
placement_group=opts.placement_group,
user_data=user_data_content,
instance_initiated_shutdown_behavior=opts.instance_initiated_shutdown_behavior,
instance_profile_name=opts.instance_profile_name)
master_nodes = master_res.instances
print("Launched master in %s, regid = %s" % (zone, master_res.id))
# This wait time corresponds to SPARK-4983
print("Waiting for AWS to propagate instance metadata...")
time.sleep(15)
# Give the instances descriptive names and set additional tags
additional_tags = {}
if opts.additional_tags.strip():
additional_tags = dict(
map(str.strip, tag.split(':', 1)) for tag in opts.additional_tags.split(',')
)
print('Applying tags to master nodes')
for master in master_nodes:
master.add_tags(
dict(additional_tags, Name='{cn}-master-{iid}'.format(cn=cluster_name, iid=master.id))
)
print('Applying tags to slave nodes')
for slave in slave_nodes:
slave.add_tags(
dict(additional_tags, Name='{cn}-slave-{iid}'.format(cn=cluster_name, iid=slave.id))
)
if opts.tag_volumes:
if len(additional_tags) > 0:
print('Applying tags to volumes')
all_instance_ids = [x.id for x in master_nodes + slave_nodes]
volumes = conn.get_all_volumes(filters={'attachment.instance-id': all_instance_ids})
for v in volumes:
v.add_tags(additional_tags)
else:
print('--tag-volumes has no effect without --additional-tags')
# Return all the instances
return (master_nodes, slave_nodes)
def get_existing_cluster(conn, opts, cluster_name, die_on_error=True):
"""
Get the EC2 instances in an existing cluster if available.
Returns a tuple of lists of EC2 instance objects for the masters and slaves.
"""
print("Searching for existing cluster {c} in region {r}...".format(
c=cluster_name, r=opts.region))
def get_instances(group_names):
"""
Get all non-terminated instances that belong to any of the provided security groups.
EC2 reservation filters and instance states are documented here:
http://docs.aws.amazon.com/cli/latest/reference/ec2/describe-instances.html#options
"""
reservations = conn.get_all_reservations(
filters={"instance.group-name": group_names})
instances = itertools.chain.from_iterable(r.instances for r in reservations)
return [i for i in instances if i.state not in ["shutting-down", "terminated"]]
master_instances = get_instances([cluster_name + "-master"])
slave_instances = get_instances([cluster_name + "-slaves"])
if any((master_instances, slave_instances)):
print("Found {m} master{plural_m}, {s} slave{plural_s}.".format(
m=len(master_instances),
plural_m=('' if len(master_instances) == 1 else 's'),
s=len(slave_instances),
plural_s=('' if len(slave_instances) == 1 else 's')))
if not master_instances and die_on_error:
print("ERROR: Could not find a master for cluster {c} in region {r}.".format(
c=cluster_name, r=opts.region), file=sys.stderr)
sys.exit(1)
return (master_instances, slave_instances)
# Deploy configuration files and run setup scripts on a newly launched
# or started EC2 cluster.
def setup_cluster(conn, master_nodes, slave_nodes, opts, deploy_ssh_key):
master = get_dns_name(master_nodes[0], opts.private_ips)
if deploy_ssh_key:
print("Generating cluster's SSH key on master...")
key_setup = """
[ -f ~/.ssh/id_rsa ] ||
(ssh-keygen -q -t rsa -N '' -f ~/.ssh/id_rsa &&
cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys)
"""
ssh(master, opts, key_setup)
dot_ssh_tar = ssh_read(master, opts, ['tar', 'c', '.ssh'])
print("Transferring cluster's SSH key to slaves...")
for slave in slave_nodes:
slave_address = get_dns_name(slave, opts.private_ips)
print(slave_address)
ssh_write(slave_address, opts, ['tar', 'x'], dot_ssh_tar)
# orginal full set of modules
# modules = ['spark', 'ephemeral-hdfs', 'persistent-hdfs',
# 'mapreduce', 'spark-standalone', 'tachyon', 'rstudio']
# install minimal set of modules
modules = ['spark', 'ephemeral-hdfs', 'spark-standalone']
if opts.hadoop_major_version == "1":
modules = list(filter(lambda x: x != "mapreduce", modules))
if opts.ganglia:
modules.append('ganglia')
# Clear SPARK_WORKER_INSTANCES if running on YARN
if opts.hadoop_major_version == "yarn":
opts.worker_instances = ""
# NOTE: We should clone the repository before running deploy_files to
# prevent ec2-variables.sh from being overwritten
print("Cloning spark-ec2 scripts from {r}/tree/{b} on master...".format(
r=opts.spark_ec2_git_repo, b=opts.spark_ec2_git_branch))
ssh(
host=master,
opts=opts,
command="rm -rf spark-ec2"
+ " && "
+ "git clone {r} -b {b} spark-ec2".format(r=opts.spark_ec2_git_repo,
b=opts.spark_ec2_git_branch)
)
print("Deploying files to master...")
deploy_files(
conn=conn,
root_dir=SPARK_EC2_DIR + "/" + "deploy.generic",
opts=opts,
master_nodes=master_nodes,
slave_nodes=slave_nodes,
modules=modules
)
if opts.deploy_root_dir is not None:
print("Deploying {s} to master...".format(s=opts.deploy_root_dir))
deploy_user_files(
root_dir=opts.deploy_root_dir,
opts=opts,
master_nodes=master_nodes
)
print("Running setup on master...")
setup_spark_cluster(master, opts)
print("Done!")
def setup_spark_cluster(master, opts):
ssh(master, opts, "chmod u+x spark-ec2/setup.sh")
ssh(master, opts, "spark-ec2/setup.sh")
print("Spark standalone cluster started at http://%s:8080" % master)
if opts.ganglia:
print("Ganglia started at http://%s:5080/ganglia" % master)
def is_ssh_available(host, opts, print_ssh_output=True):
"""
Check if SSH is available on a host.
"""
s = subprocess.Popen(
ssh_command(opts) + ['-t', '-t', '-o', 'ConnectTimeout=3',
'%s@%s' % (opts.user, host), stringify_command('true')],
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT # we pipe stderr through stdout to preserve output order
)
cmd_output = s.communicate()[0] # [1] is stderr, which we redirected to stdout
if s.returncode != 0 and print_ssh_output:
# extra leading newline is for spacing in wait_for_cluster_state()
print(textwrap.dedent("""\n
Warning: SSH connection error. (This could be temporary.)
Host: {h}
SSH return code: {r}
SSH output: {o}
""").format(
h=host,
r=s.returncode,
o=cmd_output.strip()
))
return s.returncode == 0
def is_cluster_ssh_available(cluster_instances, opts):
"""