Puppet Class: profile::hadoop::common
- Defined in:
- modules/profile/manifests/hadoop/common.pp
Overview
SPDX-License-Identifier: Apache-2.0
Class profile::hadoop::common
Configures Hadoop common configuration, the baseline for all the other services/daemons/clients. This includes the Hadoop client packages as well. The main goal of this profile is to keep all the Hadoop cluster daemons/clients in sync with one single configuration.
This profile uses some defaults that are good for a generic use case, like testing in labs, but probably not for production.
Parameters
[*zookeeper_clusters*]
List of available/configured Zookeeper clusters and their properties.
[*hadoop_clusters*]
List of available/configured Hadoop clusters and their properties.
[*hadoop_clusters_secrets*]
Hash of available/configured Hadoop clusters and their secret properties,
like passwords, etc..
The following values will be checked in the hash table only if any Yarn/HDFS/MapRed
TLS config is enabled (see in the code for the exact values).
- 'ssl_keystore_keypassword' -> Related parameter for ssl-(server|client).xml
- 'ssl_keystore_password' -> Related parameter for ssl-(server|client).xml
- 'ssl_trustore_password' -> Related parameter for ssl-(server|client).xml
Default: {}
[*hadoop_cluster_name*]
The Hadoop cluster name to pick up config properties from.
Default: 'bigtop'
[*config_override*]
Hash of Hadoop properties that override the ones defined in the
hadoop_clusters's variable configuration.
Default: {}
[*ensure_ssl_config*]
Extra argument to force the profile to not deploy TLS keys if any of the
Yarn/HDFS/MapReduce TLS config has been added. This is useful in places where
we need the TLS config to be picked (for example to use the encrypted shuffle
in map-reduce jobs) but not TLS keys are available for the host.
Default: false
Hadoop properties
These properties can be added to either hadoop_clusters or config_override's
hashes, and they configure specific Hadoop functionality.
[*zookeeper_cluster_name*]
The zookeeper cluster name to use.
[*resourcemanager_hosts*]
List of hostnames acting as Yarn Resource Managers for the cluster.
[*cluster_name*]
Name of the Hadoop cluster.
[*namenode_hosts*]
List of hostnames acting as HDFS Namenodes for the cluster.
[*journalnode_hosts*]
List of hostnames acting as HDFS Journalnodes for the cluster.
[*datanode_volumes_failed_tolerated*]
Number of disk/volume failures tolerated by the datanode before
shutting down.
Default: undef
[*hdfs_trash_checkpoint_interval*]
Number of minutes to wait before creating a trash checkpoint directory
in each home directory.
Default: undef
[*hdfs_trash_interval*]
Number of minutes to wait before considering a trash checkpoint stale/old
and hence eligible for deletion. This parameter enables the HDFS trash
functionality even without setting hdfs_trash_checkpoint_interval, but
keep in mind that its default value for hadoop will be 0 (every time the
checkpointer runs it creates a new checkpoint out of current and removes
checkpoints created more than hdfs_trash_interval minutes ago).
Default: undef
[*mapreduce_reduce_shuffle_parallelcopies*]
Map-reduce specific setting.
Default: undef
[*mapreduce_task_io_sort_mb*]
Map-reduce specific setting.
Default: undef
[*mapreduce_task_io_sort_factor*]
Map-reduce specific setting.
Default: undef
[*mapreduce_map_memory_mb*]
Map container reserved memory.
Default: undef
[*mapreduce_map_java_opts*]
Map container JVM ops settings.
Default: undef
[*mapreduce_reduce_memory_mb*]
Reduce container reserved memory.
Default: undef
[*mapreduce_reduce_java_opts*]
Reduce container JVM ops settings.
Default: undef
[*yarn_heapsize*]
Yarn Node and Resource Manager max heap size.
Default: undef
[*yarn_nodemanager_opts*]
Yarn Node Manager JVM opts.
Default: undef
[*yarn_resourcemanager_opts*]
Yarn Resource Manager JVM opts.
Default: undef
[*hadoop_heapsize*]
HDFS daemons maximum heapsize.
Default: undef
[*hadoop_datanode_opts*]
HDFS datanode JVM opts.
Default: undef
[*hadoop_journalnode_opts*]
HDFS journalnode JVM opts.
Default: undef
[*hadoop_namenode_opts*]
JVM opts to pass to the HDFS Namenode daemon.
If you change these values please check profile::hadoop::*::namenode_heapsize
since some alarms need to be tuned in the master/standby config too.
Default: undef
[*yarn_app_mapreduce_am_resource_mb*]
Yarn Application Master container size (Mb).
Default: undef
[*yarn_app_mapreduce_am_command_opts*]
Yarn Application Master JVM opts.
Default: undef
[*mapreduce_history_java_opts*]
Map-reduce History server JVM opts.
Default: undef
[*yarn_scheduler_minimum_allocation_vcores*]
Yarn scheduler specific setting.
Default: undef
[*yarn_scheduler_maximum_allocation_vcores*]
Yarn scheduler specific setting.
Default: undef
[*yarn_nodemanager_os_reserved_memory_mb*]
Map-reduce specific setting. If set, yarn_nodemanager_resource_memory_mb will
be set as total_memory_on_host - yarn_nodemanager_os_reserved_memory_mb.
Default: undef
[*yarn_scheduler_minimum_allocation_mb*]
Yarn scheduler specific setting.
Default: undef
[*yarn_scheduler_maximum_allocation_mb*]
Yarn scheduler specific setting. If not set, but reserved_memory_mb and total_memory_mb are,
This will be set to total_memory_mb - reserved_memory_mb.
Default: undef
[*java_home*]
Sets the JAVA_HOME env. variable in hadoop-env.sh
[*net_topology*]
A mapping of FQDN hostname to 'rack'. This will be used by net-topology.py.erb
to render a script that will be used for Hadoop node rack awareness.
[*datanode_mounts_prefix*]
Gets the list of partitions mounted on the host that match a given prefix
to form the list of mountpoints that Yarn and HDFS will rely on.
IMPORTANT: make sure that the partitions are mounted on the OS before using this
parameter.
Default: '/var/lib/hadoop/data'
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# File 'modules/profile/manifests/hadoop/common.pp', line 191
class profile::hadoop::common (
Hash[String, Any] $zookeeper_clusters = lookup('zookeeper_clusters'),
Hash[String, Any] $hadoop_clusters = lookup('hadoop_clusters'),
String $cluster_name = lookup('profile::hadoop::common::hadoop_cluster_name'),
Hash[String, Any] $hadoop_clusters_secrets = lookup('hadoop_clusters_secrets', { 'default_value' => {} }),
Hash[String, Any] $config_override = lookup('profile::hadoop::common::config_override', { 'default_value' => {} }),
Boolean $ensure_ssl_config = lookup('profile::hadoop::common::ensure_ssl_config', { 'default_value' => false }),
String $datanode_mounts_prefix = lookup('profile::hadoop::common::datanode_mounts_prefix', { 'default_value' => '/var/lib/hadoop/data'}),
Optional[Integer] $min_datanode_mounts = lookup('profile::hadoop::common::min_datanode_mounts', { 'default_value' => undef }),
) {
# Properties that are not meant to have undef as default value (a hash key
# without a correspondent value returns undef) should be listed in here.
$hadoop_default_config = {
'hadoop_var_directory' => '/var/lib/hadoop',
'java_home' => '/usr/lib/jvm/java-8-openjdk-amd64/jre',
'dfs_block_size' => 268435456, # 256M
}
# The final Hadoop configuration is obtained merging three hashes:
# 1) Hadoop properties with a default value different than undef
# 2) Hadoop properies meant to be shared among all Hadoop daemons/services
# 3) Hadoop properties that might get overridden by specific Hadoop role/profiles.
$hadoop_config = $hadoop_default_config + $hadoop_clusters[$cluster_name] + $config_override
# This is a hash of secrets broken down by cluster name. Useful since 1) these info, like passwords,
# cannot be retrieved from the above $hadoop_config 2) All the roles that share this profile can
# get a single source of configuration, that avoids copy/paste config around.
$hadoop_secrets_config = $hadoop_clusters_secrets[$cluster_name]
$zookeeper_cluster_name = $hadoop_config['zookeeper_cluster_name']
$yarn_resourcemanager_zk_state_store_parent_path = $hadoop_config['yarn_resourcemanager_zk_state_store_parent_path']
$yarn_resourcemanager_fs_state_store_uri = $hadoop_config['yarn_resourcemanager_fs_state_store_uri']
$resourcemanager_hosts = $hadoop_config['resourcemanager_hosts']
$namenode_hosts = $hadoop_config['namenode_hosts']
$journalnode_hosts = $hadoop_config['journalnode_hosts']
$hadoop_var_directory = $hadoop_config['hadoop_var_directory']
$datanode_volumes_failed_tolerated = $hadoop_config['datanode_volumes_failed_tolerated']
$dfs_namenode_handler_count = $hadoop_config['dfs_namenode_handler_count']
$dfs_namenode_service_handler_count = $hadoop_config['dfs_namenode_service_handler_count']
$dfs_namenode_service_port = $hadoop_config['dfs_namenode_service_port']
$dfs_block_size = $hadoop_config['dfs_block_size']
$yarn_heapsize = $hadoop_config['yarn_heapsize']
$yarn_nodemanager_opts = $hadoop_config['yarn_nodemanager_opts']
$yarn_resourcemanager_opts = $hadoop_config['yarn_resourcemanager_opts']
$hadoop_heapsize = $hadoop_config['hadoop_heapsize']
$hadoop_datanode_opts = $hadoop_config['hadoop_datanode_opts']
$hadoop_journalnode_opts = $hadoop_config['hadoop_journalnode_opts']
$hadoop_namenode_opts = $hadoop_config['hadoop_namenode_opts']
$mapreduce_history_java_opts = $hadoop_config['mapreduce_history_java_opts']
$yarn_fair_scheduler_template = $hadoop_config['yarn_fair_scheduler_template']
$yarn_node_labels_enabled = $hadoop_config['yarn_node_labels_enabled']
$yarn_nodemanager_resource_memory_mb = $hadoop_config['yarn_nodemanager_os_reserved_memory_mb'] ? {
undef => undef,
default => floor($facts['memorysize_mb']) - $hadoop_config['yarn_nodemanager_os_reserved_memory_mb'],
}
$yarn_scheduler_maximum_allocation_mb = $hadoop_config['yarn_scheduler_maximum_allocation_mb']
$java_home = $hadoop_config['java_home']
$mapreduce_reduce_shuffle_parallelcopies = $hadoop_config['mapreduce_reduce_shuffle_parallelcopies'] ? {
undef => 10,
default => $hadoop_config['mapreduce_reduce_shuffle_parallelcopies'],
}
$mapreduce_task_io_sort_mb = $hadoop_config['mapreduce_task_io_sort_mb'] ? {
undef => 200,
default => $hadoop_config['mapreduce_task_io_sort_mb'],
}
$mapreduce_task_io_sort_factor = $hadoop_config['mapreduce_task_io_sort_factor'] ? {
undef => 10,
default => $hadoop_config['mapreduce_task_io_sort_factor'],
}
# Adding sane defaults to these options in case not explicitly set via hiera.
# More info: T218758
$yarn_resourcemanager_fs_state_store_retry_policy = $hadoop_config['yarn_resourcemanager_fs_state_store_retry_policy'] ? {
undef => '2000,10',
default => $hadoop_config['yarn_resourcemanager_fs_state_store_retry_policy'],
}
$yarn_resourcemanager_max_completed_applications = $hadoop_config['yarn_resourcemanager_max_completed_applications'] ? {
undef => '5000',
default => $hadoop_config['yarn_resourcemanager_max_completed_applications'],
}
$core_site_extra_properties = $hadoop_config['core_site_extra_properties'] ? {
undef => {},
default => $hadoop_config['core_site_extra_properties'],
}
$yarn_site_extra_properties = $hadoop_config['yarn_site_extra_properties'] ? {
undef => {},
default => $hadoop_config['yarn_site_extra_properties'],
}
$hdfs_site_extra_properties = $hadoop_config['hdfs_site_extra_properties'] ? {
undef => {},
default => $hadoop_config['hdfs_site_extra_properties'],
}
$mapred_site_extra_properties = $hadoop_config['mapred_site_extra_properties'] ? {
undef => {},
default => $hadoop_config['mapred_site_extra_properties'],
}
$yarn_nm_container_executor_config = $hadoop_config['yarn_nodemanager_container_executor_config'] ? {
undef => {},
default => $hadoop_config['yarn_nm_container_executor_config'],
}
$yarn_use_spark_shuffle = $hadoop_config['yarn_use_spark_shuffle'] ? {
undef => true,
default => $hadoop_config['yarn_use_spark_shuffle'],
}
$yarn_use_multi_spark_shufflers = $hadoop_config['yarn_use_multi_spark_shufflers'] ? {
undef => false,
default => $hadoop_config['yarn_use_multi_spark_shufflers'],
}
$yarn_multi_spark_shuffler_versions = $hadoop_config['yarn_multi_spark_shuffler_versions'] ? {
undef => {},
default => $hadoop_config['yarn_multi_spark_shuffler_versions'],
}
# The HDFS Trash is configured in this way:
# 1) Once every day a checkpoint is made (that contains all the trash for a day).
# 2) After a month a checkpoint is deleted.
$hdfs_trash_checkpoint_interval = $hadoop_config['hdfs_trash_checkpoint_interval'] ? {
undef => 1440,
default => $hadoop_config['hdfs_trash_checkpoint_interval'],
}
$hdfs_trash_interval = $hadoop_config['hdfs_trash_interval'] ? {
undef => 43200,
default => $hadoop_config['hdfs_trash_interval'],
}
# These Map/Reduce and YARN ApplicationMaster master settings are
# settable per job.
# Choosing 2G for default application container size.
# Map container size and JVM max heap size (-XmX)
$mapreduce_map_memory_mb = $hadoop_config['mapreduce_map_memory_mb'] ? {
undef => 2048,
default => $hadoop_config['mapreduce_map_memory_mb'],
}
$mapreduce_map_java_opts = $hadoop_config['mapreduce_map_java_opts'] ? {
undef => '-Xmx1638m', # 0.8 * 2G
default => $hadoop_config['mapreduce_map_java_opts'],
}
# Reduce container size and JVM max heap size (-Xmx)
$mapreduce_reduce_memory_mb = $hadoop_config['mapreduce_reduce_memory_mb'] ? {
undef => '4096', # 2 * 2G
default => $hadoop_config['mapreduce_reduce_memory_mb'],
}
$mapreduce_reduce_java_opts = $hadoop_config['mapreduce_reduce_java_opts'] ? {
undef => '-Xmx3276m', # 0.8 * 2 * 2G
default => $hadoop_config['mapreduce_reduce_java_opts'],
}
# Yarn ApplicationMaster container size and max heap size (-Xmx)
$yarn_app_mapreduce_am_resource_mb = $hadoop_config['yarn_app_mapreduce_am_resource_mb'] ? {
undef => 4096, # 2 * 2G
default => $hadoop_config['yarn_app_mapreduce_am_resource_mb'],
}
$yarn_app_mapreduce_am_command_opts = $hadoop_config['yarn_app_mapreduce_am_command_opts'] ? {
undef => '-Xmx3276m', # 0.8 * 2 * 2G
default => $hadoop_config['yarn_app_mapreduce_am_command_opts'],
}
# https://issues.apache.org/jira/browse/YARN-5774
# Flink 1.1+ also needs this value to be >= 0
$yarn_scheduler_minimum_allocation_mb = $hadoop_config['yarn_scheduler_minimum_allocation_mb'] ? {
undef => 1,
default => $hadoop_config['yarn_scheduler_minimum_allocation_mb'],
}
# https://issues.apache.org/jira/browse/YARN-5774
$yarn_scheduler_minimum_allocation_vcores = $hadoop_config['yarn_scheduler_minimum_allocation_vcores'] ? {
undef => 1,
default => $hadoop_config['yarn_scheduler_minimum_allocation_vcores'],
}
$yarn_scheduler_maximum_allocation_vcores = $hadoop_config['yarn_scheduler_maximum_allocation_vcores'] ? {
undef => 32,
default => $hadoop_config['yarn_scheduler_maximum_allocation_vcores'],
}
# Raised for T206943
$yarn_resourcemanager_zk_timeout_ms = $hadoop_config['yarn_resourcemanager_zk_timeout_ms'] ? {
undef => 20000,
default => $hadoop_config['yarn_resourcemanager_zk_timeout_ms'],
}
$enable_log4j_extras = $hadoop_config['enable_log4j_extras'] ? {
undef => true,
default => $hadoop_config['enable_log4j_extras'],
}
# The datanode mountpoints are retrieved from facter, among the list of mounted
# partitions on the host. Once a partition is not available anymore (disk broken for example),
# it is sufficient to run puppet to update the configs (and restart daemons if needed).
$all_partitions = $facts['partitions'].map |$device, $partition_metadata| { $partition_metadata['mount'] }
$datanode_mounts = $all_partitions.filter |$partitions| { $datanode_mounts_prefix in $partitions }
# Fail-safe for Hadoop workers only meant to avoid running a datanode with a low number of partition by mistake.
# The minimum number of datanode partitions is set via hiera following:
# Number of datanode partitions - disk failures tolerated
if $min_datanode_mounts and length($datanode_mounts) < $min_datanode_mounts {
fail("Number of datanode mountpoints (${datanode_mounts.length}) below threshold: ${min_datanode_mounts}, please check.")
}
# Include Wikimedia's thirdparty/bigtop apt component
# as an apt source on all Hadoop hosts.
require ::profile::bigtop::apt
# Need Java before Hadoop is installed.
Class['profile::java'] -> Class['profile::hadoop::common']
$hadoop_name_directory = "${hadoop_var_directory}/name"
$hadoop_data_directory = "${hadoop_var_directory}/data"
$hadoop_journal_directory = "${hadoop_var_directory}/journal"
$zookeeper_hosts = keys($zookeeper_clusters[$zookeeper_cluster_name]['hosts'])
# If specified, this will be rendered into the net-topology.py.erb script.
$net_topology = $hadoop_config['net_topology']
$net_topology_script_content = $net_topology ? {
undef => undef,
default => template('profile/hadoop/net-topology.py.erb'),
}
$core_site_extra_properties_default = {
'hadoop.ssl.enabled.protocols' => 'TLSv1.2',
'hadoop.rpc.protection' => 'privacy',
'hadoop.security.authentication' => 'kerberos',
# https://www.cloudera.com/documentation/enterprise/5-16-x/topics/cdh_sg_hiveserver2_security.html#concept_vxf_pgx_nm
'hadoop.proxyuser.hive.hosts' => '*',
'hadoop.proxyuser.hive.groups' => '*',
'hadoop.proxyuser.presto.hosts' => '*',
'hadoop.proxyuser.presto.groups' => '*',
'hadoop.proxyuser.superset.hosts' => '*',
'hadoop.proxyuser.superset.groups' =>'*',
'fs.permissions.umask-mode' => '027',
}
$yarn_site_extra_properties_default = {
# After upgrading to CDH 5.4.0, we are encountering this bug:
# https://issues.apache.org/jira/browse/MAPREDUCE-5799
# This should work around the problem.
'yarn.app.mapreduce.am.env' => 'LD_LIBRARY_PATH=/usr/lib/hadoop/lib/native',
# The default of 90.0 for this was marking older dells as unhealthy when they still
# had 2TB of space left. 99% will mark them at unhealthy with they still have
# > 200G free.
'yarn.nodemanager.disk-health-checker.max-disk-utilization-per-disk-percentage' => '99.0',
'yarn.resourcemanager.principal' => 'yarn/_HOST@WIKIMEDIA',
'yarn.nodemanager.principal' => 'yarn/_HOST@WIKIMEDIA',
'yarn.resourcemanager.keytab' => '/etc/security/keytabs/hadoop/yarn.keytab',
'yarn.nodemanager.keytab' => '/etc/security/keytabs/hadoop/yarn.keytab',
'yarn.nodemanager.linux-container-executor.group' => 'yarn',
'yarn.nodemanager.container-executor.class' => 'org.apache.hadoop.yarn.server.nodemanager.LinuxContainerExecutor',
'spark.authenticate' => true,
'spark.network.crypto.enabled' => true,
# We tried to bump the yarn.nodemanager.vmem-pmem-ratio to 10.1 in T278441,
# but in several use cases Spark containers were killed due to excessive vmem usage
# (but not the same for pmem). Bumping the ratio even more is not productive,
# it is more efficient to just disable the vmem check.
'yarn.nodemanager.vmem-check-enabled' => false,
}
$yarn_nodemanager_container_executor_config_default = {
'yarn.nodemanager.linux-container-executor.group' => 'yarn',
'min.user.id' => '100',
# hdfs is allowed to make distCP working (mapred user that can be started by hdfs
# to be able to avoid permission issues while copying).
'allowed.system.users' => 'hive,hdfs',
'banned.users' => 'root,yarn,mapred,bin,nobody',
}
$hdfs_site_extra_properties_default = {
'dfs.cluster.administrators' => 'hdfs analytics-admins,ops',
'dfs.block.access.token.enable' => 'true',
'dfs.namenode.keytab.file' => '/etc/security/keytabs/hadoop/hdfs.keytab',
'dfs.secondary.namenode.keytab.file' => '/etc/security/keytabs/hadoop/hdfs.keytab',
'dfs.namenode.kerberos.principal' => 'hdfs/_HOST@WIKIMEDIA',
'dfs.secondary.namenode.kerberos.principal' => 'hdfs/_HOST@WIKIMEDIA',
'dfs.journalnode.keytab.file' => '/etc/security/keytabs/hadoop/hdfs.keytab',
'dfs.journalnode.kerberos.principal' => 'hdfs/_HOST@WIKIMEDIA',
'dfs.journalnode.kerberos.internal.spnego.principal' => 'HTTP/_HOST@WIKIMEDIA',
'dfs.web.authentication.kerberos.keytab' => '/etc/security/keytabs/hadoop/HTTP.keytab',
'dfs.web.authentication.kerberos.principal' => 'HTTP/_HOST@WIKIMEDIA',
'dfs.datanode.keytab.file' => '/etc/security/keytabs/hadoop/hdfs.keytab',
'dfs.datanode.kerberos.principal' => 'hdfs/_HOST@WIKIMEDIA',
'dfs.encrypt.data.transfer' => 'true',
'dfs.data.transfer.protection' => 'privacy',
# This is required to allow the datanode to start:
# https://hadoop.apache.org/docs/r2.6.0/hadoop-project-dist/hadoop-common/SecureMode.html#Secure_DataNode
'dfs.http.policy' => 'HTTPS_ONLY',
'dfs.encrypt.data.transfer.cipher.suites' => 'AES/CTR/NoPadding',
'dfs.encrypt.data.transfer.cipher.key.bitlength' => '128',
}
$mapred_site_extra_properties_default = {
'mapreduce.ssl.enabled' => true,
'mapreduce.shuffle.ssl.enabled' => true,
'mapreduce.jobhistory.principal' => 'mapred/_HOST@WIKIMEDIA',
'mapreduce.jobhistory.keytab' => '/etc/security/keytabs/hadoop/mapred.keytab',
}
class { 'bigtop::hadoop':
# Default to using running resourcemanager on the same hosts
# as the namenodes.
resourcemanager_hosts => $resourcemanager_hosts,
zookeeper_hosts => $zookeeper_hosts,
yarn_resourcemanager_zk_timeout_ms => $yarn_resourcemanager_zk_timeout_ms,
yarn_resourcemanager_zk_state_store_parent_path => $yarn_resourcemanager_zk_state_store_parent_path,
yarn_resourcemanager_fs_state_store_uri => $yarn_resourcemanager_fs_state_store_uri,
yarn_resourcemanager_fs_state_store_retry_policy => $yarn_resourcemanager_fs_state_store_retry_policy,
yarn_resourcemanager_max_completed_applications => $yarn_resourcemanager_max_completed_applications,
dfs_name_dir => [$hadoop_name_directory],
dfs_journalnode_edits_dir => $hadoop_journal_directory,
dfs_datanode_failed_volumes_tolerated => $datanode_volumes_failed_tolerated,
fs_trash_checkpoint_interval => $hdfs_trash_checkpoint_interval,
fs_trash_interval => $hdfs_trash_interval,
dfs_namenode_handler_count => $dfs_namenode_handler_count,
dfs_namenode_service_handler_count => $dfs_namenode_service_handler_count,
dfs_namenode_service_port => $dfs_namenode_service_port,
cluster_name => $cluster_name,
namenode_hosts => $namenode_hosts,
journalnode_hosts => $journalnode_hosts,
datanode_mounts => $datanode_mounts,
yarn_heapsize => $yarn_heapsize,
hadoop_heapsize => $hadoop_heapsize,
yarn_nodemanager_opts => $yarn_nodemanager_opts,
yarn_resourcemanager_opts => $yarn_resourcemanager_opts,
hadoop_namenode_opts => $hadoop_namenode_opts,
hadoop_datanode_opts => $hadoop_datanode_opts,
hadoop_journalnode_opts => $hadoop_journalnode_opts,
mapreduce_history_java_opts => $mapreduce_history_java_opts,
yarn_app_mapreduce_am_resource_mb => $yarn_app_mapreduce_am_resource_mb,
yarn_app_mapreduce_am_command_opts => $yarn_app_mapreduce_am_command_opts,
yarn_nodemanager_resource_memory_mb => $yarn_nodemanager_resource_memory_mb,
yarn_scheduler_minimum_allocation_mb => $yarn_scheduler_minimum_allocation_mb,
yarn_scheduler_maximum_allocation_mb => $yarn_scheduler_maximum_allocation_mb,
yarn_scheduler_minimum_allocation_vcores => $yarn_scheduler_minimum_allocation_vcores,
yarn_scheduler_maximum_allocation_vcores => $yarn_scheduler_maximum_allocation_vcores,
yarn_use_spark_shuffle => $yarn_use_spark_shuffle,
yarn_use_multi_spark_shufflers => $yarn_use_multi_spark_shufflers,
yarn_multi_spark_shuffler_versions => $yarn_multi_spark_shuffler_versions,
yarn_node_labels_enabled => $yarn_node_labels_enabled,
dfs_block_size => 268435456, # 256 MB
io_file_buffer_size => 131072,
# Turn on Snappy compression by default for maps and final outputs
mapreduce_intermediate_compression_codec => 'org.apache.hadoop.io.compress.SnappyCodec',
mapreduce_output_compression => true,
mapreduce_output_compression_codec => 'org.apache.hadoop.io.compress.SnappyCodec',
mapreduce_output_compression_type => 'BLOCK',
mapreduce_job_reuse_jvm_num_tasks => 1,
mapreduce_reduce_shuffle_parallelcopies => $mapreduce_reduce_shuffle_parallelcopies,
mapreduce_task_io_sort_mb => $mapreduce_task_io_sort_mb,
mapreduce_task_io_sort_factor => $mapreduce_task_io_sort_factor,
mapreduce_map_memory_mb => $mapreduce_map_memory_mb,
mapreduce_map_java_opts => $mapreduce_map_java_opts,
mapreduce_reduce_memory_mb => $mapreduce_reduce_memory_mb,
mapreduce_reduce_java_opts => $mapreduce_reduce_java_opts,
net_topology_script_content => $net_topology_script_content,
net_topology => $net_topology,
# This needs to be set in order to use Impala
dfs_datanode_hdfs_blocks_metadata_enabled => true,
# Whether or not to use fair-scheduler.xml.erb to define FairScheduler queues.
fair_scheduler_template => $yarn_fair_scheduler_template,
# Yarn App Master possible port ranges
yarn_app_mapreduce_am_job_client_port_range => '55000-55199',
core_site_extra_properties => $core_site_extra_properties_default + $core_site_extra_properties,
yarn_site_extra_properties => $yarn_site_extra_properties_default + $yarn_site_extra_properties,
hdfs_site_extra_properties => $hdfs_site_extra_properties_default + $hdfs_site_extra_properties,
mapred_site_extra_properties => $mapred_site_extra_properties_default + $mapred_site_extra_properties,
yarn_nodemanager_container_executor_config => $yarn_nodemanager_container_executor_config_default + $yarn_nm_container_executor_config,
java_home => $java_home,
enable_log4j_extras => $enable_log4j_extras,
}
# The following code deploys TLS certificates to the Hadoop cluster hosts.
# Very important note too keep in mind:
# "Ensure that common name (CN) matches exactly with the fully qualified domain name (FQDN) of the server.
# The client compares the CN with the DNS domain name to ensure
# that it is indeed connecting to the desired server, not the malicious one."
# Source: https://it.hortonworks.com/blog/deploying-https-hdfs/
# When 'ensure_ssl_config' is set to true, the following assumptions are made for
# the puppet private repository:
# 1) TLS certificates are not needed since we use the host's puppet ones.
# 2) There is puppet code that copies the host's puppet TLS cert into a pks12 keystore (with custom
# password, see below) to a known location.
# 3) keystores/trustores are all encrypted with the passwords stated in the $hadoop_clusters_secrets
# hash (stored in the private repo as well).
# Also please remember that the configuration below takes care of deploying the trustores/keystores and
# the related ssl-(client|server).xml configs, but it does not enable any TLS setting for Yarn/HDFS.
# In order to do it, specific settings to the main hadoop_clusters hiera config need to be made.
#
if $ensure_ssl_config {
$hadoop_ssl_config_name = "hadoop_${cluster_name}"
$hostname_suffix = $::realm ? {
'labs' => '.eqiad.wmflabs',
default => "${::site}.wmnet",
}
$keystore_type = 'pkcs12'
$keystore_password = $hadoop_secrets_config['ssl_keystore_password']
# The keystore password is needed for the Journalnode to start,
# since not adding it or using an empty value lead to null pointer
# exceptions. Even if the key in the keystore is not pretected by a password,
# the setting needs to be present anyway. Upstream tutorials suggest to
# put this value equal to the value of the keystore password.
$keystore_keypassword = $hadoop_secrets_config['ssl_keystore_keypassword']
$keystore_path = "${bigtop::hadoop::config_directory}/ssl/server.p12"
# TODO: consider using profile::pki::get_cert
puppet::expose_agent_certs{$bigtop::hadoop::config_directory:
user => 'root',
group => 'hadoop',
provide_p12 => true,
provide_pem => false,
p12_password => $keystore_password,
}
$ssl_server_config = {
'ssl.server.keystore.type' => $keystore_type,
'ssl.server.keystore.keypassword' => $keystore_keypassword,
'ssl.server.keystore.password' => $keystore_password,
'ssl.server.keystore.location' => $keystore_path,
}
# By default we ensure that the puppet CA is trusted in the default
# JVM's truststore. No need for ssl-client.xml config in this case.
class { 'bigtop::hadoop::ssl_config':
config_directory => $::bigtop::hadoop::config_directory,
ssl_server_config => $ssl_server_config,
}
}
# Starting with Bullseye the systemd unit for systemd-logind uses ProtectSystem=strict,
# which doesn't work with HDFS, so exclude /mnt from the list of inaccessible paths for
# the systemd-logind service
if debian::codename::ge('bullseye') {
systemd::unit { 'systemd-logind.service':
content => "[Service]\nInaccessiblePaths=-/mnt\n",
restart => false,
override => true,
}
}
if $::realm == 'labs' {
# Hadoop directories in labs should be created by puppet.
# This conditional could be added to each worker,master,standby
# classes, but since it doesn't hurt to have these directories
# in labs, and since I don't want to add the $::realm conditionals
# in each class, I do it here.
file { [
$hadoop_var_directory,
$hadoop_data_directory,
]:
ensure => 'directory',
before => Class['bigtop::hadoop'],
}
}
contain 'bigtop::hadoop'
}
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