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Posted to commits@ambari.apache.org by ao...@apache.org on 2017/01/11 16:08:04 UTC
[2/6] ambari git commit: AMBARI-19171. Configuring YARN with custom
queues leads to misleading errors in Stack Advisor (aonishuk)
http://git-wip-us.apache.org/repos/asf/ambari/blob/dda16576/ambari-server/src/main/resources/stacks/HDP/2.5/services/stack_advisor.py
----------------------------------------------------------------------
diff --git a/ambari-server/src/main/resources/stacks/HDP/2.5/services/stack_advisor.py b/ambari-server/src/main/resources/stacks/HDP/2.5/services/stack_advisor.py
index f244cb9..45a5351 100644
--- a/ambari-server/src/main/resources/stacks/HDP/2.5/services/stack_advisor.py
+++ b/ambari-server/src/main/resources/stacks/HDP/2.5/services/stack_advisor.py
@@ -18,13 +18,13 @@ limitations under the License.
"""
import math
-import traceback
from ambari_commons.str_utils import string_set_equals
from resource_management.core.logger import Logger
from resource_management.core.exceptions import Fail
from resource_management.libraries.functions.get_bare_principal import get_bare_principal
+
class HDP25StackAdvisor(HDP24StackAdvisor):
def __init__(self):
@@ -94,7 +94,7 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
parentItems = super(HDP25StackAdvisor, self).getComponentLayoutValidations(services, hosts)
childItems = []
- hsi_hosts = self.__getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
+ hsi_hosts = self.getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
if len(hsi_hosts) > 1:
message = "Only one host can install HIVE_SERVER_INTERACTIVE. "
childItems.append(
@@ -139,14 +139,12 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
"item": self.getWarnItem(
"Should be set to recommended value to report metrics to Ambari Metrics service.")})
-
return self.toConfigurationValidationProblems(validationItems, "storm-site")
def validateAtlasConfigurations(self, properties, recommendedDefaults, configurations, services, hosts):
- application_properties = getSiteProperties(configurations, "application-properties")
+ application_properties = self.getSiteProperties(configurations, "application-properties")
validationItems = []
- #<editor-fold desc="LDAP and AD">
auth_type = application_properties['atlas.authentication.method.ldap.type']
auth_ldap_enable = application_properties['atlas.authentication.method.ldap'].lower() == 'true'
Logger.info("Validating Atlas configs, authentication type: %s" % str(auth_type))
@@ -183,7 +181,6 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
if prop not in application_properties or application_properties[prop] is None or application_properties[prop].strip() == "":
validationItems.append({"config-name": prop,
"item": self.getErrorItem("If authentication type is %s, this property is required." % auth_type)})
- #</editor-fold>
if application_properties['atlas.graph.index.search.backend'] == 'solr5' and \
not application_properties['atlas.graph.index.search.solr.zookeeper-url']:
@@ -252,13 +249,13 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
def validateYarnConfigurations(self, properties, recommendedDefaults, configurations, services, hosts):
parentValidationProblems = super(HDP25StackAdvisor, self).validateYARNConfigurations(properties, recommendedDefaults, configurations, services, hosts)
- yarn_site_properties = getSiteProperties(configurations, "yarn-site")
+ yarn_site_properties = self.getSiteProperties(configurations, "yarn-site")
servicesList = [service["StackServices"]["service_name"] for service in services["services"]]
componentsListList = [service["components"] for service in services["services"]]
componentsList = [item["StackServiceComponents"] for sublist in componentsListList for item in sublist]
validationItems = []
- hsi_hosts = self.__getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
+ hsi_hosts = self.getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
if len(hsi_hosts) > 0:
# HIVE_SERVER_INTERACTIVE is mapped to a host
if 'yarn.resourcemanager.work-preserving-recovery.enabled' not in yarn_site_properties or \
@@ -271,124 +268,116 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
validationProblems.extend(parentValidationProblems)
return validationProblems
- """
- Does the following validation checks for HIVE_SERVER_INTERACTIVE's hive-interactive-site configs.
- 1. Queue selected in 'hive.llap.daemon.queue.name' config should be sized >= to minimum required to run LLAP
- and Hive2 app.
- 2. Queue selected in 'hive.llap.daemon.queue.name' config state should not be 'STOPPED'.
- 3. 'hive.server2.enable.doAs' config should be set to 'false' for Hive2.
- 4. 'Maximum Total Concurrent Queries'(hive.server2.tez.sessions.per.default.queue) should not consume more that 50% of selected queue for LLAP.
- 5. if 'llap' queue is selected, in order to run Service Checks, 'remaining available capacity' in cluster is atleast 512 MB.
- """
def validateHiveInteractiveSiteConfigurations(self, properties, recommendedDefaults, configurations, services, hosts):
+ """
+ Does the following validation checks for HIVE_SERVER_INTERACTIVE's hive-interactive-site configs.
+ 1. Queue selected in 'hive.llap.daemon.queue.name' config should be sized >= to minimum required to run LLAP
+ and Hive2 app.
+ 2. Queue selected in 'hive.llap.daemon.queue.name' config state should not be 'STOPPED'.
+ 3. 'hive.server2.enable.doAs' config should be set to 'false' for Hive2.
+ 4. 'Maximum Total Concurrent Queries'(hive.server2.tez.sessions.per.default.queue) should not consume more that 50% of selected queue for LLAP.
+ 5. if 'llap' queue is selected, in order to run Service Checks, 'remaining available capacity' in cluster is atleast 512 MB.
+ """
validationItems = []
- hsi_hosts = self.__getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
- curr_selected_queue_for_llap = None
- curr_selected_queue_for_llap_cap_perc = None
+ hsi_hosts = self.getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
+ llap_queue_name = None
+ llap_queue_cap_perc = None
MIN_ASSUMED_CAP_REQUIRED_FOR_SERVICE_CHECKS = 512
- current_selected_queue_for_llap_cap = None
+ llap_queue_cap = None
+ hsi_site = self.getServicesSiteProperties(services, self.HIVE_INTERACTIVE_SITE)
- if len(hsi_hosts) > 0:
- # Get total cluster capacity
- node_manager_host_list = self.get_node_manager_hosts(services, hosts)
- node_manager_cnt = len(node_manager_host_list)
- yarn_nm_mem_in_mb = self.get_yarn_nm_mem_in_mb(services, configurations)
- total_cluster_capacity = node_manager_cnt * yarn_nm_mem_in_mb
+ if len(hsi_hosts) == 0:
+ return []
- capacity_scheduler_properties, received_as_key_value_pair = self.getCapacitySchedulerProperties(services)
- if capacity_scheduler_properties:
- if self.HIVE_INTERACTIVE_SITE in services['configurations'] and \
- 'hive.llap.daemon.queue.name' in services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']:
- curr_selected_queue_for_llap = services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']['hive.llap.daemon.queue.name']
- if curr_selected_queue_for_llap:
- current_selected_queue_for_llap_cap = self.__getSelectedQueueTotalCap(capacity_scheduler_properties,
- curr_selected_queue_for_llap, total_cluster_capacity)
- if current_selected_queue_for_llap_cap:
- curr_selected_queue_for_llap_cap_perc = int(current_selected_queue_for_llap_cap * 100 / total_cluster_capacity)
- min_reqd_queue_cap_perc = self.min_queue_perc_reqd_for_llap_and_hive_app(services, hosts, configurations)
-
- # Validate that the selected queue in 'hive.llap.daemon.queue.name' should be sized >= to minimum required
- # to run LLAP and Hive2 app.
- if curr_selected_queue_for_llap_cap_perc < min_reqd_queue_cap_perc:
- errMsg1 = "Selected queue '{0}' capacity ({1}%) is less than minimum required capacity ({2}%) for LLAP " \
- "app to run".format(curr_selected_queue_for_llap, curr_selected_queue_for_llap_cap_perc, min_reqd_queue_cap_perc)
- validationItems.append({"config-name": "hive.llap.daemon.queue.name","item": self.getErrorItem(errMsg1)})
- else:
- Logger.error("Couldn't retrieve '{0}' queue's capacity from 'capacity-scheduler' while doing validation checks for "
- "Hive Server Interactive.".format(curr_selected_queue_for_llap))
-
- # Validate that current selected queue in 'hive.llap.daemon.queue.name' state is not STOPPED.
- llap_selected_queue_state = self.__getQueueStateFromCapacityScheduler(capacity_scheduler_properties, curr_selected_queue_for_llap)
- if llap_selected_queue_state:
- if llap_selected_queue_state == "STOPPED":
- errMsg2 = "Selected queue '{0}' current state is : '{1}'. It is required to be in 'RUNNING' state for LLAP to run"\
- .format(curr_selected_queue_for_llap, llap_selected_queue_state)
- validationItems.append({"config-name": "hive.llap.daemon.queue.name","item": self.getErrorItem(errMsg2)})
- else:
- Logger.error("Couldn't retrieve '{0}' queue's state from 'capacity-scheduler' while doing validation checks for "
- "Hive Server Interactive.".format(curr_selected_queue_for_llap))
- else:
- Logger.error("Couldn't retrieve current selection for 'hive.llap.daemon.queue.name' while doing validation "
- "checks for Hive Server Interactive.")
+ # Get total cluster capacity
+ node_manager_host_list = self.getHostsForComponent(services, "YARN", "NODEMANAGER")
+ node_manager_cnt = len(node_manager_host_list)
+ yarn_nm_mem_in_mb = self.get_yarn_nm_mem_in_mb(services, configurations)
+ total_cluster_cap = node_manager_cnt * yarn_nm_mem_in_mb
+ capacity_scheduler_properties, received_as_key_value_pair = self.getCapacitySchedulerProperties(services)
+
+ if not capacity_scheduler_properties:
+ Logger.warning("Couldn't retrieve 'capacity-scheduler' properties while doing validation checks for Hive Server Interactive.")
+ return []
+
+ if hsi_site:
+ if "hive.llap.daemon.queue.name" in hsi_site and hsi_site['hive.llap.daemon.queue.name']:
+ llap_queue_name = hsi_site['hive.llap.daemon.queue.name']
+ llap_queue_cap = self.__getSelectedQueueTotalCap(capacity_scheduler_properties, llap_queue_name, total_cluster_cap)
+
+ if llap_queue_cap:
+ llap_queue_cap_perc = float(llap_queue_cap * 100 / total_cluster_cap)
+ min_reqd_queue_cap_perc = self.min_queue_perc_reqd_for_llap_and_hive_app(services, hosts, configurations)
+
+ # Validate that the selected queue in 'hive.llap.daemon.queue.name' should be sized >= to minimum required
+ # to run LLAP and Hive2 app.
+ if llap_queue_cap_perc < min_reqd_queue_cap_perc:
+ errMsg1 = "Selected queue '{0}' capacity ({1}%) is less than minimum required capacity ({2}%) for LLAP " \
+ "app to run".format(llap_queue_name, llap_queue_cap_perc, min_reqd_queue_cap_perc)
+ validationItems.append({"config-name": "hive.llap.daemon.queue.name", "item": self.getErrorItem(errMsg1)})
else:
- Logger.error("Couldn't retrieve 'hive.llap.daemon.queue.name' config from 'hive-interactive-site' while doing "
- "validation checks for Hive Server Interactive.")
- pass
+ Logger.error("Couldn't retrieve '{0}' queue's capacity from 'capacity-scheduler' while doing validation checks for "
+ "Hive Server Interactive.".format(llap_queue_name))
+
+ # Validate that current selected queue in 'hive.llap.daemon.queue.name' state is not STOPPED.
+ llap_selected_queue_state = self.__getQueueStateFromCapacityScheduler(capacity_scheduler_properties, llap_queue_name)
+ if llap_selected_queue_state:
+ if llap_selected_queue_state == "STOPPED":
+ errMsg2 = "Selected queue '{0}' current state is : '{1}'. It is required to be in 'RUNNING' state for LLAP to run"\
+ .format(llap_queue_name, llap_selected_queue_state)
+ validationItems.append({"config-name": "hive.llap.daemon.queue.name","item": self.getErrorItem(errMsg2)})
+ else:
+ Logger.error("Couldn't retrieve '{0}' queue's state from 'capacity-scheduler' while doing validation checks for "
+ "Hive Server Interactive.".format(llap_queue_name))
else:
- Logger.error("Couldn't retrieve 'capacity-scheduler' properties while doing validation checks for Hive Server Interactive.")
- pass
-
- if self.HIVE_INTERACTIVE_SITE in services['configurations']:
- # Validate that 'hive.server2.enable.doAs' config is not set to 'true' for Hive2.
- if 'hive.server2.enable.doAs' in services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']:
- hive2_enable_do_as = services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']['hive.server2.enable.doAs']
- if hive2_enable_do_as == 'true':
- validationItems.append({"config-name": "hive.server2.enable.doAs","item": self.getErrorItem("Value should be set to 'false' for Hive2.")})
-
- # Validate that 'Maximum Total Concurrent Queries'(hive.server2.tez.sessions.per.default.queue) is not consuming more that
- # 50% of selected queue for LLAP.
- if current_selected_queue_for_llap_cap and 'hive.server2.tez.sessions.per.default.queue' in \
- services['configurations']['hive-interactive-site']['properties']:
- num_tez_sessions = services['configurations']['hive-interactive-site']['properties']['hive.server2.tez.sessions.per.default.queue']
- if num_tez_sessions:
- num_tez_sessions = long(num_tez_sessions)
- yarn_min_container_size = self.get_yarn_min_container_size(services, configurations)
- tez_am_container_size = self.calculate_tez_am_container_size(services, long(total_cluster_capacity))
- normalized_tez_am_container_size = self._normalizeUp(tez_am_container_size, yarn_min_container_size)
- llap_selected_queue_cap_remaining = current_selected_queue_for_llap_cap - (normalized_tez_am_container_size * num_tez_sessions)
- if llap_selected_queue_cap_remaining <= current_selected_queue_for_llap_cap/2:
- errMsg3 = " Reducing the 'Maximum Total Concurrent Queries' (value: {0}) is advisable as it is consuming more than 50% of " \
- "'{1}' queue for LLAP.".format(num_tez_sessions, curr_selected_queue_for_llap)
- validationItems.append({"config-name": "hive.server2.tez.sessions.per.default.queue","item": self.getWarnItem(errMsg3)})
-
- # Validate that 'remaining available capacity' in cluster is atleast 512 MB, after 'llap' queue is selected,
- # in order to run Service Checks.
- if curr_selected_queue_for_llap and curr_selected_queue_for_llap_cap_perc and \
- curr_selected_queue_for_llap == self.AMBARI_MANAGED_LLAP_QUEUE_NAME:
- curr_selected_queue_for_llap_cap = float(curr_selected_queue_for_llap_cap_perc) / 100 * total_cluster_capacity
- available_cap_in_cluster = total_cluster_capacity - curr_selected_queue_for_llap_cap
- if available_cap_in_cluster < MIN_ASSUMED_CAP_REQUIRED_FOR_SERVICE_CHECKS:
- errMsg4 = "Capacity used by '{0}' queue is '{1}'. Service checks may not run as remaining available capacity " \
- "({2}) in cluster is less than 512 MB.".format(self.AMBARI_MANAGED_LLAP_QUEUE_NAME, curr_selected_queue_for_llap_cap, available_cap_in_cluster)
- validationItems.append({"config-name": "hive.llap.daemon.queue.name","item": self.getWarnItem(errMsg4)})
+ Logger.error("Couldn't retrieve 'hive.llap.daemon.queue.name' config from 'hive-interactive-site' while doing "
+ "validation checks for Hive Server Interactive.")
+
+ # Validate that 'hive.server2.enable.doAs' config is not set to 'true' for Hive2.
+ if 'hive.server2.enable.doAs' in hsi_site and hsi_site['hive.server2.enable.doAs'] == "true":
+ validationItems.append({"config-name": "hive.server2.enable.doAs", "item": self.getErrorItem("Value should be set to 'false' for Hive2.")})
+
+ # Validate that 'Maximum Total Concurrent Queries'(hive.server2.tez.sessions.per.default.queue) is not consuming more that
+ # 50% of selected queue for LLAP.
+ if llap_queue_cap and 'hive.server2.tez.sessions.per.default.queue' in hsi_site:
+ num_tez_sessions = hsi_site['hive.server2.tez.sessions.per.default.queue']
+ if num_tez_sessions:
+ num_tez_sessions = long(num_tez_sessions)
+ yarn_min_container_size = long(self.get_yarn_min_container_size(services, configurations))
+ tez_am_container_size = self.calculate_tez_am_container_size(services, long(total_cluster_cap))
+ normalized_tez_am_container_size = self._normalizeUp(tez_am_container_size, yarn_min_container_size)
+ llap_selected_queue_cap_remaining = llap_queue_cap - (normalized_tez_am_container_size * num_tez_sessions)
+ if llap_selected_queue_cap_remaining <= llap_queue_cap/2:
+ errMsg3 = " Reducing the 'Maximum Total Concurrent Queries' (value: {0}) is advisable as it is consuming more than 50% of " \
+ "'{1}' queue for LLAP.".format(num_tez_sessions, llap_queue_name)
+ validationItems.append({"config-name": "hive.server2.tez.sessions.per.default.queue","item": self.getWarnItem(errMsg3)})
+
+ # Validate that 'remaining available capacity' in cluster is at least 512 MB, after 'llap' queue is selected,
+ # in order to run Service Checks.
+ if llap_queue_name and llap_queue_cap_perc and llap_queue_name == self.AMBARI_MANAGED_LLAP_QUEUE_NAME:
+ curr_selected_queue_for_llap_cap = float(llap_queue_cap_perc) / 100 * total_cluster_cap
+ available_cap_in_cluster = total_cluster_cap - curr_selected_queue_for_llap_cap
+ if available_cap_in_cluster < MIN_ASSUMED_CAP_REQUIRED_FOR_SERVICE_CHECKS:
+ errMsg4 = "Capacity used by '{0}' queue is '{1}'. Service checks may not run as remaining available capacity " \
+ "({2}) in cluster is less than 512 MB.".format(self.AMBARI_MANAGED_LLAP_QUEUE_NAME, curr_selected_queue_for_llap_cap, available_cap_in_cluster)
+ validationItems.append({"config-name": "hive.llap.daemon.queue.name","item": self.getWarnItem(errMsg4)})
validationProblems = self.toConfigurationValidationProblems(validationItems, "hive-interactive-site")
return validationProblems
def validateHiveInteractiveEnvConfigurations(self, properties, recommendedDefaults, configurations, services, hosts):
- hive_site_env_properties = getSiteProperties(configurations, "hive-interactive-env")
+ hive_site_env_properties = self.getSiteProperties(configurations, "hive-interactive-env")
validationItems = []
- hsi_hosts = self.__getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
+ hsi_hosts = self.getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
if len(hsi_hosts) > 0:
# HIVE_SERVER_INTERACTIVE is mapped to a host
if 'enable_hive_interactive' not in hive_site_env_properties or (
- 'enable_hive_interactive' in hive_site_env_properties and hive_site_env_properties[
- 'enable_hive_interactive'].lower() != 'true'):
+ 'enable_hive_interactive' in hive_site_env_properties and
+ hive_site_env_properties['enable_hive_interactive'].lower() != 'true'):
+
validationItems.append({"config-name": "enable_hive_interactive",
"item": self.getErrorItem(
"HIVE_SERVER_INTERACTIVE requires enable_hive_interactive in hive-interactive-env set to true.")})
- pass
-
else:
# no HIVE_SERVER_INTERACTIVE
if 'enable_hive_interactive' in hive_site_env_properties and hive_site_env_properties[
@@ -396,8 +385,6 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
validationItems.append({"config-name": "enable_hive_interactive",
"item": self.getErrorItem(
"enable_hive_interactive in hive-interactive-env should be set to false.")})
- pass
- pass
validationProblems = self.toConfigurationValidationProblems(validationItems, "hive-interactive-env")
return validationProblems
@@ -437,15 +424,15 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
def recommendStormConfigurations(self, configurations, clusterData, services, hosts):
super(HDP25StackAdvisor, self).recommendStormConfigurations(configurations, clusterData, services, hosts)
- storm_site = getServicesSiteProperties(services, "storm-site")
+ storm_site = self.getServicesSiteProperties(services, "storm-site")
putStormSiteProperty = self.putProperty(configurations, "storm-site", services)
putStormSiteAttributes = self.putPropertyAttribute(configurations, "storm-site")
security_enabled = (storm_site is not None and "storm.zookeeper.superACL" in storm_site)
-
+
if security_enabled:
_storm_principal_name = services['configurations']['storm-env']['properties']['storm_principal_name']
storm_bare_jaas_principal = get_bare_principal(_storm_principal_name)
- if 'nimbus.impersonation.acl' in storm_site:
+ if 'nimbus.impersonation.acl' in storm_site:
storm_nimbus_impersonation_acl = storm_site["nimbus.impersonation.acl"]
storm_nimbus_impersonation_acl.replace('{{storm_bare_jaas_principal}}', storm_bare_jaas_principal)
putStormSiteProperty('nimbus.impersonation.acl', storm_nimbus_impersonation_acl)
@@ -612,7 +599,7 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
if 'atlas-env' in services['configurations']:
atlas_server_metadata_size = 50000
if 'atlas_server_metadata_size' in services['configurations']['atlas-env']['properties']:
- atlas_server_metadata_size = int(services['configurations']['atlas-env']['properties']['atlas_server_metadata_size'])
+ atlas_server_metadata_size = float(services['configurations']['atlas-env']['properties']['atlas_server_metadata_size'])
atlas_server_xmx = 2048
@@ -669,47 +656,42 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
putHiveInteractiveEnvPropertyAttribute = self.putPropertyAttribute(configurations, "hive-interactive-env")
# For 'Hive Server Interactive', if the component exists.
- hsi_hosts = self.__getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
+ hsi_hosts = self.getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
+ hsi_properties = self.getServicesSiteProperties(services, self.HIVE_INTERACTIVE_SITE)
+
if len(hsi_hosts) > 0:
- hsi_host = hsi_hosts[0]
putHiveInteractiveEnvProperty('enable_hive_interactive', 'true')
# Update 'hive.llap.daemon.queue.name' property attributes if capacity scheduler is changed.
- if self.HIVE_INTERACTIVE_SITE in services['configurations']:
- if 'hive.llap.daemon.queue.name' in services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']:
+ if hsi_properties and 'hive.llap.daemon.queue.name' in hsi_properties:
self.setLlapDaemonQueuePropAttributes(services, configurations)
- # Update 'hive.server2.tez.default.queues' value
- hive_tez_default_queue = None
- if 'hive-interactive-site' in configurations and \
- 'hive.llap.daemon.queue.name' in configurations[self.HIVE_INTERACTIVE_SITE]['properties']:
- hive_tez_default_queue = configurations[self.HIVE_INTERACTIVE_SITE]['properties']['hive.llap.daemon.queue.name']
- Logger.info("'hive.llap.daemon.queue.name' value from configurations : '{0}'".format(hive_tez_default_queue))
- if not hive_tez_default_queue:
- hive_tez_default_queue = services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']['hive.llap.daemon.queue.name']
- Logger.info("'hive.llap.daemon.queue.name' value from services : '{0}'".format(hive_tez_default_queue))
+ hsi_conf_properties = self.getSiteProperties(configurations, self.HIVE_INTERACTIVE_SITE)
+
+ hive_tez_default_queue = hsi_properties["hive.llap.daemon.queue.name"]
+ if hsi_conf_properties and "hive.llap.daemon.queue.name" in hsi_conf_properties:
+ hive_tez_default_queue = hsi_conf_properties['hive.llap.daemon.queue.name']
+
if hive_tez_default_queue:
putHiveInteractiveSiteProperty("hive.server2.tez.default.queues", hive_tez_default_queue)
- Logger.info("Updated 'hive.server2.tez.default.queues' config : '{0}'".format(hive_tez_default_queue))
+ Logger.debug("Updated 'hive.server2.tez.default.queues' config : '{0}'".format(hive_tez_default_queue))
else:
putHiveInteractiveEnvProperty('enable_hive_interactive', 'false')
putHiveInteractiveEnvPropertyAttribute("num_llap_nodes", "visible", "false")
- if self.HIVE_INTERACTIVE_SITE in services['configurations'] and \
- 'hive.llap.zk.sm.connectionString' in services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']:
- # Fill the property 'hive.llap.zk.sm.connectionString' required by Hive Server Interactive (HiveServer2)
+ if hsi_properties and "hive.llap.zk.sm.connectionString" in hsi_properties:
zookeeper_host_port = self.getZKHostPortString(services)
if zookeeper_host_port:
putHiveInteractiveSiteProperty("hive.llap.zk.sm.connectionString", zookeeper_host_port)
- pass
def recommendYARNConfigurations(self, configurations, clusterData, services, hosts):
super(HDP25StackAdvisor, self).recommendYARNConfigurations(configurations, clusterData, services, hosts)
+ hsi_env_poperties = self.getServicesSiteProperties(services, "hive-interactive-env")
+ cluster_env = self.getServicesSiteProperties(services, "cluster-env")
# Queue 'llap' creation/removal logic (Used by Hive Interactive server and associated LLAP)
- if 'hive-interactive-env' in services['configurations'] and \
- 'enable_hive_interactive' in services['configurations']['hive-interactive-env']['properties']:
- enable_hive_interactive = services['configurations']['hive-interactive-env']['properties']['enable_hive_interactive']
+ if hsi_env_poperties and 'enable_hive_interactive' in hsi_env_poperties:
+ enable_hive_interactive = hsi_env_poperties['enable_hive_interactive']
LLAP_QUEUE_NAME = 'llap'
# Hive Server interactive is already added or getting added
@@ -720,8 +702,8 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
putYarnSiteProperty = self.putProperty(configurations, "yarn-site", services)
stack_root = "/usr/hdp"
- if "cluster-env" in services["configurations"] and "stack_root" in services["configurations"]["cluster-env"]["properties"]:
- stack_root = services["configurations"]["cluster-env"]["properties"]["stack_root"]
+ if cluster_env and "stack_root" in cluster_env:
+ stack_root = cluster_env["stack_root"]
timeline_plugin_classes_values = []
timeline_plugin_classpath_values = []
@@ -736,546 +718,457 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
putYarnSiteProperty('yarn.timeline-service.entity-group-fs-store.group-id-plugin-classes', ",".join(timeline_plugin_classes_values))
putYarnSiteProperty('yarn.timeline-service.entity-group-fs-store.group-id-plugin-classpath', ":".join(timeline_plugin_classpath_values))
- """
- Entry point for updating Hive's 'LLAP app' configs namely : (1). num_llap_nodes (2). hive.llap.daemon.yarn.container.mb
- (3). hive.llap.daemon.num.executors (4). hive.llap.io.memory.size (5). llap_heap_size (6). slider_am_container_mb,
- (7). hive.server2.tez.sessions.per.default.queue, (8). tez.am.resource.memory.mb (9). hive.tez.container.size
- (10). tez.runtime.io.sort.mb (11). tez.runtime.unordered.output.buffer.size-mb (12). hive.llap.io.threadpool.size, and
- (13). hive.llap.io.enabled.
+ def updateLlapConfigs(self, configurations, services, hosts, llap_queue_name):
+ """
+ Entry point for updating Hive's 'LLAP app' configs namely :
+ (1). num_llap_nodes (2). hive.llap.daemon.yarn.container.mb
+ (3). hive.llap.daemon.num.executors (4). hive.llap.io.memory.size (5). llap_heap_size (6). slider_am_container_mb,
+ (7). hive.server2.tez.sessions.per.default.queue, (8). tez.am.resource.memory.mb (9). hive.tez.container.size
+ (10). tez.runtime.io.sort.mb (11). tez.runtime.unordered.output.buffer.size-mb (12). hive.llap.io.threadpool.size, and
+ (13). hive.llap.io.enabled.
- The trigger point for updating LLAP configs (mentioned above) is change in values of any of the following:
- (1). 'enable_hive_interactive' set to 'true' (2). 'num_llap_nodes' (3). 'hive.server2.tez.sessions.per.default.queue'
- (4). Change in queue selection for config 'hive.llap.daemon.queue.name'.
+ The trigger point for updating LLAP configs (mentioned above) is change in values of any of the following:
+ (1). 'enable_hive_interactive' set to 'true' (2). 'num_llap_nodes' (3). 'hive.server2.tez.sessions.per.default.queue'
+ (4). Change in queue selection for config 'hive.llap.daemon.queue.name'.
- If change in value for 'num_llap_nodes' or 'hive.server2.tez.sessions.per.default.queue' is detected, that config
- value is not calulated, but read and use in calculation for dependent configs.
+ If change in value for 'num_llap_nodes' or 'hive.server2.tez.sessions.per.default.queue' is detected, that config
+ value is not calulated, but read and use in calculation for dependent configs.
- Note: All memory caluclations are in MB, unless specified otherwise.
- """
- def updateLlapConfigs(self, configurations, services, hosts, llap_queue_name):
- Logger.info("Entered updateLlapConfigs() ..")
+ Note: All memory calculations are in MB, unless specified otherwise.
+ """
putHiveInteractiveSiteProperty = self.putProperty(configurations, self.HIVE_INTERACTIVE_SITE, services)
putHiveInteractiveSitePropertyAttribute = self.putPropertyAttribute(configurations, self.HIVE_INTERACTIVE_SITE)
-
putHiveInteractiveEnvProperty = self.putProperty(configurations, "hive-interactive-env", services)
putHiveInteractiveEnvPropertyAttribute = self.putPropertyAttribute(configurations, "hive-interactive-env")
-
putTezInteractiveSiteProperty = self.putProperty(configurations, "tez-interactive-site", services)
-
llap_daemon_selected_queue_name = None
- selected_queue_is_ambari_managed_llap = None # Queue named 'llap' at root level is Ambari managed.
+ selected_queue_is_ambari_managed_llap = None # Queue named 'llap' at root level is Ambari managed.
llap_selected_queue_am_percent = None
DEFAULT_EXECUTOR_TO_AM_RATIO = 20
MIN_EXECUTOR_TO_AM_RATIO = 10
MAX_CONCURRENT_QUERIES = 32
leafQueueNames = None
MB_TO_BYTES = 1048576
+ hsi_site = self.getServicesSiteProperties(services, self.HIVE_INTERACTIVE_SITE)
+ yarn_site = self.getServicesSiteProperties(services, "yarn-site")
# Update 'hive.llap.daemon.queue.name' prop combo entries
self.setLlapDaemonQueuePropAttributes(services, configurations)
if not services["changed-configurations"]:
read_llap_daemon_yarn_cont_mb = long(self.get_yarn_min_container_size(services, configurations))
- putHiveInteractiveSiteProperty('hive.llap.daemon.yarn.container.mb', read_llap_daemon_yarn_cont_mb)
- # initial memory setting to make sure hive.llap.daemon.yarn.container.mb >= yarn.scheduler.minimum-allocation-mb
- Logger.info("Adjusted 'hive.llap.daemon.yarn.container.mb' to yarn min container size as initial size "
- "(" + str(self.get_yarn_min_container_size(services, configurations)) + " MB).")
+ putHiveInteractiveSiteProperty("hive.llap.daemon.yarn.container.mb", read_llap_daemon_yarn_cont_mb)
- try:
- if self.HIVE_INTERACTIVE_SITE in services['configurations'] and \
- 'hive.llap.daemon.queue.name' in services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']:
- llap_daemon_selected_queue_name = services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']['hive.llap.daemon.queue.name']
+ if hsi_site and "hive.llap.daemon.queue.name" in hsi_site:
+ llap_daemon_selected_queue_name = hsi_site["hive.llap.daemon.queue.name"]
- # Update Visibility of 'num_llap_nodes' slider. Visible only if selected queue is Ambari created 'llap'.
- capacity_scheduler_properties, received_as_key_value_pair = self.getCapacitySchedulerProperties(services)
- if capacity_scheduler_properties:
- # Get all leaf queues.
- leafQueueNames = self.getAllYarnLeafQueues(capacity_scheduler_properties)
- Logger.info("YARN leaf Queues = {0}".format(leafQueueNames))
- if len(leafQueueNames) == 0:
- raise Fail("Queue(s) couldn't be retrieved from capacity-scheduler.")
-
- # Check if it's 1st invocation after enabling Hive Server Interactive (config: enable_hive_interactive).
- changed_configs_has_enable_hive_int = self.are_config_props_in_changed_configs(services, "hive-interactive-env",
- set(['enable_hive_interactive']), False)
- llap_named_queue_selected_in_curr_invocation = None
- if changed_configs_has_enable_hive_int \
- and services['configurations']['hive-interactive-env']['properties']['enable_hive_interactive']:
- if (len(leafQueueNames) == 1 or (len(leafQueueNames) == 2 and llap_queue_name in leafQueueNames)):
- llap_named_queue_selected_in_curr_invocation = True
- putHiveInteractiveSiteProperty('hive.llap.daemon.queue.name', llap_queue_name)
- putHiveInteractiveSiteProperty('hive.server2.tez.default.queues', llap_queue_name)
- Logger.info("'hive.llap.daemon.queue.name' and 'hive.server2.tez.default.queues' values set as : {0}".format(llap_queue_name))
- else:
- first_leaf_queue = list(leafQueueNames)[0] # 1st invocation, pick the 1st leaf queue and set it as selected.
- putHiveInteractiveSiteProperty('hive.llap.daemon.queue.name', first_leaf_queue)
- putHiveInteractiveSiteProperty('hive.server2.tez.default.queues', first_leaf_queue)
- llap_named_queue_selected_in_curr_invocation = False
- Logger.info("'hive.llap.daemon.queue.name' and 'hive.server2.tez.default.queues' values set as : {0}".format(first_leaf_queue))
- Logger.info("llap_named_queue_selected_in_curr_invocation = {0}".format(llap_named_queue_selected_in_curr_invocation))
-
- if (len(leafQueueNames) == 2 and (llap_daemon_selected_queue_name != None and llap_daemon_selected_queue_name == llap_queue_name) or \
- llap_named_queue_selected_in_curr_invocation) or \
- (len(leafQueueNames) == 1 and llap_daemon_selected_queue_name == 'default' and llap_named_queue_selected_in_curr_invocation):
- putHiveInteractiveEnvPropertyAttribute("num_llap_nodes", "visible", "true")
- Logger.info("Selected YARN queue for LLAP is : '{0}'. Current YARN queues : {1}. Setting 'Number of LLAP nodes' "
- "slider visibility to 'True'".format(llap_queue_name, list(leafQueueNames)))
- selected_queue_is_ambari_managed_llap = True
+ # Update Visibility of 'num_llap_nodes' slider. Visible only if selected queue is Ambari created 'llap'.
+ capacity_scheduler_properties, received_as_key_value_pair = self.getCapacitySchedulerProperties(services)
+ if capacity_scheduler_properties:
+ # Get all leaf queues.
+ leafQueueNames = self.getAllYarnLeafQueues(capacity_scheduler_properties)
+ Logger.info("YARN leaf Queues = {0}".format(leafQueueNames))
+ if len(leafQueueNames) == 0:
+ Logger.error("Queue(s) couldn't be retrieved from capacity-scheduler.")
+ return
+
+ # Check if it's 1st invocation after enabling Hive Server Interactive (config: enable_hive_interactive).
+ changed_configs_has_enable_hive_int = self.isConfigPropertiesChanged(services, "hive-interactive-env", ['enable_hive_interactive'], False)
+ llap_named_queue_selected_in_curr_invocation = None
+ if changed_configs_has_enable_hive_int \
+ and services['configurations']['hive-interactive-env']['properties']['enable_hive_interactive']:
+ if len(leafQueueNames) == 1 or (len(leafQueueNames) == 2 and llap_queue_name in leafQueueNames):
+ llap_named_queue_selected_in_curr_invocation = True
+ putHiveInteractiveSiteProperty('hive.llap.daemon.queue.name', llap_queue_name)
+ putHiveInteractiveSiteProperty('hive.server2.tez.default.queues', llap_queue_name)
else:
- putHiveInteractiveEnvPropertyAttribute("num_llap_nodes", "visible", "false")
- Logger.info("Selected YARN queue for LLAP is : '{0}'. Current YARN queues : {1}. Setting 'Number of LLAP nodes' "
- "visibility to 'False'.".format(llap_daemon_selected_queue_name, list(leafQueueNames)))
- selected_queue_is_ambari_managed_llap = False
-
- if not llap_named_queue_selected_in_curr_invocation: # We would be creating the 'llap' queue later. Thus, cap-sched doesn't have
- # state information pertaining to 'llap' queue.
- # Check: State of the selected queue should not be STOPPED.
- if llap_daemon_selected_queue_name:
- llap_selected_queue_state = self.__getQueueStateFromCapacityScheduler(capacity_scheduler_properties, llap_daemon_selected_queue_name)
- if llap_selected_queue_state == None or llap_selected_queue_state == "STOPPED":
- raise Fail("Selected LLAP app queue '{0}' current state is : '{1}'. Setting LLAP configs to default "
- "values.".format(llap_daemon_selected_queue_name, llap_selected_queue_state))
- else:
- raise Fail("Retrieved LLAP app queue name is : '{0}'. Setting LLAP configs to default values."
- .format(llap_daemon_selected_queue_name))
+ first_leaf_queue = list(leafQueueNames)[0] # 1st invocation, pick the 1st leaf queue and set it as selected.
+ putHiveInteractiveSiteProperty('hive.llap.daemon.queue.name', first_leaf_queue)
+ putHiveInteractiveSiteProperty('hive.server2.tez.default.queues', first_leaf_queue)
+ llap_named_queue_selected_in_curr_invocation = False
+
+ if (len(leafQueueNames) == 2 and (llap_daemon_selected_queue_name and llap_daemon_selected_queue_name == llap_queue_name) or
+ llap_named_queue_selected_in_curr_invocation) or \
+ (len(leafQueueNames) == 1 and llap_daemon_selected_queue_name == 'default' and llap_named_queue_selected_in_curr_invocation):
+ putHiveInteractiveEnvPropertyAttribute("num_llap_nodes", "visible", "true")
+ selected_queue_is_ambari_managed_llap = True
else:
- Logger.error("Couldn't retrieve 'capacity-scheduler' properties while doing YARN queue adjustment for Hive Server Interactive."
- " Not calculating LLAP configs.")
+ putHiveInteractiveEnvPropertyAttribute("num_llap_nodes", "visible", "false")
+ selected_queue_is_ambari_managed_llap = False
+
+ if not llap_named_queue_selected_in_curr_invocation: # We would be creating the 'llap' queue later. Thus, cap-sched doesn't have
+ # state information pertaining to 'llap' queue.
+ # Check: State of the selected queue should not be STOPPED.
+ if llap_daemon_selected_queue_name:
+ llap_selected_queue_state = self.__getQueueStateFromCapacityScheduler(capacity_scheduler_properties, llap_daemon_selected_queue_name)
+ if llap_selected_queue_state is None or llap_selected_queue_state == "STOPPED":
+ Logger.error("Selected LLAP app queue '{0}' current state is : '{1}'. Setting LLAP configs to default "
+ "values.".format(llap_daemon_selected_queue_name, llap_selected_queue_state))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
+ else:
+ Logger.error("Retrieved LLAP app queue name is : '{0}'. Setting LLAP configs to default values."
+ .format(llap_daemon_selected_queue_name))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
+ else:
+ Logger.error("Couldn't retrieve 'capacity-scheduler' properties while doing YARN queue adjustment for Hive Server Interactive."
+ " Not calculating LLAP configs.")
+ return
+
+ changed_configs_in_hive_int_env = None
+ llap_concurrency_in_changed_configs = None
+ llap_daemon_queue_in_changed_configs = None
+ # Calculations are triggered only if there is change in any one of the following props :
+ # 'num_llap_nodes', 'enable_hive_interactive', 'hive.server2.tez.sessions.per.default.queue'
+ # or 'hive.llap.daemon.queue.name' has change in value selection.
+ # OR
+ # services['changed-configurations'] is empty implying that this is the Blueprint call. (1st invocation)
+ if 'changed-configurations' in services.keys():
+ config_names_to_be_checked = set(['num_llap_nodes', 'enable_hive_interactive'])
+ changed_configs_in_hive_int_env = self.isConfigPropertiesChanged(services, "hive-interactive-env", config_names_to_be_checked, False)
+
+ # Determine if there is change detected in "hive-interactive-site's" configs based on which we calculate llap configs.
+ llap_concurrency_in_changed_configs = self.isConfigPropertiesChanged(services, self.HIVE_INTERACTIVE_SITE, ['hive.server2.tez.sessions.per.default.queue'], False)
+ llap_daemon_queue_in_changed_configs = self.isConfigPropertiesChanged(services, self.HIVE_INTERACTIVE_SITE, ['hive.llap.daemon.queue.name'], False)
+
+ if not changed_configs_in_hive_int_env and not llap_concurrency_in_changed_configs and \
+ not llap_daemon_queue_in_changed_configs and services["changed-configurations"]:
+
+ return
+
+ node_manager_host_list = self.getHostsForComponent(services, "YARN", "NODEMANAGER")
+ node_manager_cnt = len(node_manager_host_list)
+ yarn_nm_mem_in_mb = self.get_yarn_nm_mem_in_mb(services, configurations)
+ total_cluster_capacity = node_manager_cnt * yarn_nm_mem_in_mb
+ yarn_min_container_size = float(self.get_yarn_min_container_size(services, configurations))
+ tez_am_container_size = self.calculate_tez_am_container_size(services, long(total_cluster_capacity))
+ normalized_tez_am_container_size = self._normalizeUp(tez_am_container_size, yarn_min_container_size)
+
+ if yarn_site and "yarn.nodemanager.resource.cpu-vcores" in yarn_site:
+ cpu_per_nm_host = float(yarn_site["yarn.nodemanager.resource.cpu-vcores"])
+ else:
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
+
+ # Calculate the available memory for LLAP app
+ yarn_nm_mem_in_mb_normalized = self._normalizeDown(yarn_nm_mem_in_mb, yarn_min_container_size)
+ mem_per_thread_for_llap = self.calculate_mem_per_thread_for_llap(services, yarn_nm_mem_in_mb_normalized, cpu_per_nm_host)
+
+ if mem_per_thread_for_llap is None:
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
+
+ mem_per_thread_for_llap = float(mem_per_thread_for_llap)
+
+ if not selected_queue_is_ambari_managed_llap:
+ llap_daemon_selected_queue_cap = self.__getSelectedQueueTotalCap(capacity_scheduler_properties, llap_daemon_selected_queue_name, total_cluster_capacity)
+
+ if llap_daemon_selected_queue_cap <= 0:
+ Logger.warning("'{0}' queue capacity percentage retrieved = {1}. Expected > 0.".format(
+ llap_daemon_selected_queue_name, llap_daemon_selected_queue_cap))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
return
- changed_configs_in_hive_int_env = None
- llap_concurrency_in_changed_configs = None
- llap_daemon_queue_in_changed_configs = None
- # Calculations are triggered only if there is change in any one of the following props :
- # 'num_llap_nodes', 'enable_hive_interactive', 'hive.server2.tez.sessions.per.default.queue'
- # or 'hive.llap.daemon.queue.name' has change in value selection.
- # OR
- # services['changed-configurations'] is empty implying that this is the Blueprint call. (1st invocation)
- if 'changed-configurations' in services.keys():
- config_names_to_be_checked = set(['num_llap_nodes', 'enable_hive_interactive'])
- changed_configs_in_hive_int_env = self.are_config_props_in_changed_configs(services, "hive-interactive-env",
- config_names_to_be_checked, False)
-
- # Determine if there is change detected in "hive-interactive-site's" configs based on which we calculate llap configs.
- llap_concurrency_in_changed_configs = self.are_config_props_in_changed_configs(services, "hive-interactive-site",
- set(['hive.server2.tez.sessions.per.default.queue']), False)
- llap_daemon_queue_in_changed_configs = self.are_config_props_in_changed_configs(services, "hive-interactive-site",
- set(['hive.llap.daemon.queue.name']), False)
-
- if not changed_configs_in_hive_int_env and \
- not llap_concurrency_in_changed_configs and \
- not llap_daemon_queue_in_changed_configs and \
- services["changed-configurations"]:
- Logger.info("LLAP parameters not modified. Not adjusting LLAP configs.")
- Logger.info("Current 'changed-configuration' received is : {0}".format(services["changed-configurations"]))
+ total_llap_mem_normalized = self._normalizeDown(llap_daemon_selected_queue_cap, yarn_min_container_size)
+ num_llap_nodes_requested = math.floor(total_llap_mem_normalized / yarn_nm_mem_in_mb_normalized)
+ queue_am_fraction_perc = float(self.__getQueueAmFractionFromCapacityScheduler(capacity_scheduler_properties, llap_daemon_selected_queue_name))
+ hive_tez_am_cap_available = queue_am_fraction_perc * total_llap_mem_normalized
+ else: # Ambari managed 'llap' named queue at root level.
+ num_llap_nodes_requested = self.get_num_llap_nodes(services, configurations) #Input
+ total_llap_mem = num_llap_nodes_requested * yarn_nm_mem_in_mb_normalized
+ total_llap_mem_normalized = float(self._normalizeDown(total_llap_mem, yarn_min_container_size))
+
+ # What percent is 'total_llap_mem' of 'total_cluster_capacity' ?
+ llap_named_queue_cap_fraction = math.ceil(total_llap_mem_normalized / total_cluster_capacity * 100)
+
+ if llap_named_queue_cap_fraction > 100:
+ Logger.warning("Calculated '{0}' queue size = {1}. Cannot be > 100.".format(llap_queue_name, llap_named_queue_cap_fraction))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
return
- Logger.info("\nPerforming LLAP config calculations ......")
- node_manager_host_list = self.get_node_manager_hosts(services, hosts)
- node_manager_cnt = len(node_manager_host_list)
- yarn_nm_mem_in_mb = self.get_yarn_nm_mem_in_mb(services, configurations)
- total_cluster_capacity = node_manager_cnt * yarn_nm_mem_in_mb
- Logger.info("Calculated total_cluster_capacity : {0}, using following : node_manager_cnt : {1}, "
- "yarn_nm_mem_in_mb : {2}".format(total_cluster_capacity, node_manager_cnt, yarn_nm_mem_in_mb))
-
- yarn_min_container_size = self.get_yarn_min_container_size(services, configurations)
-
- tez_am_container_size = self.calculate_tez_am_container_size(services, long(total_cluster_capacity))
- normalized_tez_am_container_size = self._normalizeUp(tez_am_container_size, yarn_min_container_size)
- cpu_per_nm_host = self.get_cpu_per_nm_host(services)
- Logger.info("Calculated normalized_tez_am_container_size : {0}, using following : tez_am_container_size : {1}, "
- "total_cluster_capacity : {2}".format(normalized_tez_am_container_size, tez_am_container_size,
- total_cluster_capacity))
-
- # Calculate the available memory for LLAP app
- yarn_nm_mem_in_mb_normalized = self._normalizeDown(yarn_nm_mem_in_mb, yarn_min_container_size)
- mem_per_thread_for_llap = self.calculate_mem_per_thread_for_llap(services, yarn_nm_mem_in_mb_normalized, cpu_per_nm_host)
- Logger.info("Calculated mem_per_thread_for_llap : {0}, using following: yarn_nm_mem_in_mb_normalized : {1}, "
- "cpu_per_nm_host : {2}".format(mem_per_thread_for_llap, yarn_nm_mem_in_mb_normalized, cpu_per_nm_host))
-
- Logger.info("selected_queue_is_ambari_managed_llap = {0}".format(selected_queue_is_ambari_managed_llap))
- if not selected_queue_is_ambari_managed_llap:
- llap_daemon_selected_queue_cap = self.__getSelectedQueueTotalCap(capacity_scheduler_properties, llap_daemon_selected_queue_name, total_cluster_capacity)
- assert(llap_daemon_selected_queue_cap > 0, "'{0}' queue capacity percentage retrieved = {1}. "
- "Expected > 0.".format(llap_daemon_selected_queue_name, llap_daemon_selected_queue_cap))
- total_llap_mem_normalized = self._normalizeDown(llap_daemon_selected_queue_cap, yarn_min_container_size)
- Logger.info("Calculated '{0}' queue available capacity : {1}, using following: llap_daemon_selected_queue_cap : {2}, "
- "yarn_min_container_size : {3}".format(llap_daemon_selected_queue_name, total_llap_mem_normalized,
- llap_daemon_selected_queue_cap, yarn_min_container_size))
- num_llap_nodes_requested = math.floor(total_llap_mem_normalized / yarn_nm_mem_in_mb_normalized)
- Logger.info("Calculated 'num_llap_nodes_requested' : {0}, using following: total_llap_mem_normalized : {1}, "
- "yarn_nm_mem_in_mb_normalized : {2}".format(num_llap_nodes_requested, total_llap_mem_normalized, yarn_nm_mem_in_mb_normalized))
- queue_am_fraction_perc = float(self.__getQueueAmFractionFromCapacityScheduler(capacity_scheduler_properties, llap_daemon_selected_queue_name))
- hive_tez_am_cap_available = queue_am_fraction_perc * total_llap_mem_normalized
- Logger.info("Calculated 'hive_tez_am_cap_available' : {0}, using following: queue_am_fraction_perc : {1}, "
- "total_llap_mem_normalized : {2}".format(hive_tez_am_cap_available, queue_am_fraction_perc, total_llap_mem_normalized))
- else: # Ambari managed 'llap' named queue at root level.
- num_llap_nodes_requested = self.get_num_llap_nodes(services, configurations) #Input
- total_llap_mem = num_llap_nodes_requested * yarn_nm_mem_in_mb_normalized
- Logger.info("Calculated 'total_llap_mem' : {0}, using following: num_llap_nodes_requested : {1}, "
- "yarn_nm_mem_in_mb_normalized : {2}".format(total_llap_mem, num_llap_nodes_requested, yarn_nm_mem_in_mb_normalized))
- total_llap_mem_normalized = float(self._normalizeDown(total_llap_mem, yarn_min_container_size))
- Logger.info("Calculated 'total_llap_mem_normalized' : {0}, using following: total_llap_mem : {1}, "
- "yarn_min_container_size : {2}".format(total_llap_mem_normalized, total_llap_mem, yarn_min_container_size))
- # What percent is 'total_llap_mem' of 'total_cluster_capacity' ?
- llap_named_queue_cap_fraction = math.ceil(total_llap_mem_normalized / total_cluster_capacity * 100)
- assert(llap_named_queue_cap_fraction <= 100), "Calculated '{0}' queue size = {1}. Cannot be > 100.".format(llap_queue_name, llap_named_queue_cap_fraction)
- Logger.info("Calculated '{0}' queue capacity percent = {1}.".format(llap_queue_name, llap_named_queue_cap_fraction))
- # Adjust capacity scheduler for the 'llap' named queue.
- self.checkAndManageLlapQueue(services, configurations, hosts, llap_queue_name, llap_named_queue_cap_fraction)
- hive_tez_am_cap_available = total_llap_mem_normalized
- Logger.info("hive_tez_am_cap_available : {0}".format(hive_tez_am_cap_available))
-
- #Common calculations now, irrespective of the queue selected.
-
- # Get calculated value for Slider AM container Size
- slider_am_container_size = self._normalizeUp(self.calculate_slider_am_size(yarn_min_container_size),
- yarn_min_container_size)
- Logger.info("Calculated 'slider_am_container_size' : {0}, using following: yarn_min_container_size : "
- "{1}".format(slider_am_container_size, yarn_min_container_size))
-
- llap_mem_for_tezAm_and_daemons = total_llap_mem_normalized - slider_am_container_size
- assert (llap_mem_for_tezAm_and_daemons >= 2 * yarn_min_container_size), "Not enough capacity available on the cluster to run LLAP"
- Logger.info("Calculated 'llap_mem_for_tezAm_and_daemons' : {0}, using following : total_llap_mem_normalized : {1}, "
- "slider_am_container_size : {2}".format(llap_mem_for_tezAm_and_daemons, total_llap_mem_normalized, slider_am_container_size))
-
-
- # Calculate llap concurrency (i.e. Number of Tez AM's)
- max_executors_per_node = self.get_max_executors_per_node(yarn_nm_mem_in_mb_normalized, cpu_per_nm_host, mem_per_thread_for_llap)
-
- # Read 'hive.server2.tez.sessions.per.default.queue' prop if it's in changed-configs, else calculate it.
- if not llap_concurrency_in_changed_configs:
- assert(max_executors_per_node > 0), "Calculated 'max_executors_per_node' = {1}. Expected value >= 1.".format(max_executors_per_node)
- Logger.info("Calculated 'max_executors_per_node' : {0}, using following: yarn_nm_mem_in_mb_normalized : {1}, cpu_per_nm_host : {2}, "
- "mem_per_thread_for_llap: {3}".format(max_executors_per_node, yarn_nm_mem_in_mb_normalized, cpu_per_nm_host, mem_per_thread_for_llap))
- # Default 1 AM for every 20 executor threads.
- # The second part of the min calculates based on mem required for DEFAULT_EXECUTOR_TO_AM_RATIO executors + 1 AM,
- # making use of total memory. However, it's possible that total memory will not be used - and the numExecutors is
- # instead limited by #CPUs. Use maxPerNode to factor this in.
- llap_concurreny_limit = min(math.floor(max_executors_per_node * num_llap_nodes_requested / DEFAULT_EXECUTOR_TO_AM_RATIO), MAX_CONCURRENT_QUERIES)
- Logger.info("Calculated 'llap_concurreny_limit' : {0}, using following : max_executors_per_node : {1}, num_llap_nodes_requested : {2}, DEFAULT_EXECUTOR_TO_AM_RATIO "
- ": {3}, MAX_CONCURRENT_QUERIES : {4}".format(llap_concurreny_limit, max_executors_per_node, num_llap_nodes_requested, DEFAULT_EXECUTOR_TO_AM_RATIO, MAX_CONCURRENT_QUERIES))
- llap_concurrency = min(llap_concurreny_limit, math.floor(llap_mem_for_tezAm_and_daemons / (DEFAULT_EXECUTOR_TO_AM_RATIO * mem_per_thread_for_llap + normalized_tez_am_container_size)))
- Logger.info("Calculated 'llap_concurrency' : {0}, using following : llap_concurreny_limit : {1}, llap_mem_for_tezAm_and_daemons : "
- "{2}, DEFAULT_EXECUTOR_TO_AM_RATIO : {3}, mem_per_thread_for_llap : {4}, normalized_tez_am_container_size : "
- "{5}".format(llap_concurrency, llap_concurreny_limit, llap_mem_for_tezAm_and_daemons, DEFAULT_EXECUTOR_TO_AM_RATIO,
- mem_per_thread_for_llap, normalized_tez_am_container_size))
- if (llap_concurrency == 0):
- llap_concurrency = 1
- Logger.info("Adjusted 'llap_concurrency' : 1.")
-
- if (llap_concurrency * normalized_tez_am_container_size > hive_tez_am_cap_available):
- llap_concurrency = math.floor(hive_tez_am_cap_available / normalized_tez_am_container_size)
- assert(llap_concurrency > 0), "Calculated 'LLAP Concurrent Queries' = {0}. Expected value >= 1.".format(llap_concurrency)
- Logger.info("Adjusted 'llap_concurrency' : {0}, using following: hive_tez_am_cap_available : {1}, normalized_tez_am_container_size: "
- "{2}".format(llap_concurrency, hive_tez_am_cap_available, normalized_tez_am_container_size))
- else:
- # Read current value
- if 'hive.server2.tez.sessions.per.default.queue' in services['configurations'][self.HIVE_INTERACTIVE_SITE][
- 'properties']:
- llap_concurrency = long(services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties'][
- 'hive.server2.tez.sessions.per.default.queue'])
- assert (llap_concurrency >= 1), "'hive.server2.tez.sessions.per.default.queue' current value : {0}. Expected value : >= 1" \
- .format(llap_concurrency)
- Logger.info("Read 'llap_concurrency' : {0}".format(llap_concurrency ))
- else:
- raise Fail(
- "Couldn't retrieve Hive Server interactive's 'hive.server2.tez.sessions.per.default.queue' config.")
-
- # Calculate 'Max LLAP Consurrency', irrespective of whether 'llap_concurrency' was read or calculated.
- max_llap_concurreny_limit = min(math.floor(max_executors_per_node * num_llap_nodes_requested / MIN_EXECUTOR_TO_AM_RATIO), MAX_CONCURRENT_QUERIES)
- Logger.info("Calculated 'max_llap_concurreny_limit' : {0}, using following : max_executors_per_node : {1}, num_llap_nodes_requested "
- ": {2}, MIN_EXECUTOR_TO_AM_RATIO : {3}, MAX_CONCURRENT_QUERIES : {4}".format(max_llap_concurreny_limit, max_executors_per_node,
- num_llap_nodes_requested, MIN_EXECUTOR_TO_AM_RATIO,
- MAX_CONCURRENT_QUERIES))
- max_llap_concurreny = min(max_llap_concurreny_limit, math.floor(llap_mem_for_tezAm_and_daemons / (MIN_EXECUTOR_TO_AM_RATIO *
- mem_per_thread_for_llap + normalized_tez_am_container_size)))
- Logger.info("Calculated 'max_llap_concurreny' : {0}, using following : max_llap_concurreny_limit : {1}, llap_mem_for_tezAm_and_daemons : "
- "{2}, MIN_EXECUTOR_TO_AM_RATIO : {3}, mem_per_thread_for_llap : {4}, normalized_tez_am_container_size : "
- "{5}".format(max_llap_concurreny, max_llap_concurreny_limit, llap_mem_for_tezAm_and_daemons, MIN_EXECUTOR_TO_AM_RATIO,
- mem_per_thread_for_llap, normalized_tez_am_container_size))
- if (max_llap_concurreny == 0):
- max_llap_concurreny = 1
- Logger.info("Adjusted 'max_llap_concurreny' : 1.")
-
- if (max_llap_concurreny * normalized_tez_am_container_size > hive_tez_am_cap_available):
- max_llap_concurreny = math.floor(hive_tez_am_cap_available / normalized_tez_am_container_size)
- assert(max_llap_concurreny > 0), "Calculated 'Max. LLAP Concurrent Queries' = {0}. Expected value > 1".format(max_llap_concurreny)
- Logger.info("Adjusted 'max_llap_concurreny' : {0}, using following: hive_tez_am_cap_available : {1}, normalized_tez_am_container_size: "
- "{2}".format(max_llap_concurreny, hive_tez_am_cap_available, normalized_tez_am_container_size))
-
-
- # Calculate value for 'num_llap_nodes', an across cluster config.
- tez_am_memory_required = llap_concurrency * normalized_tez_am_container_size
- Logger.info("Calculated 'tez_am_memory_required' : {0}, using following : llap_concurrency : {1}, normalized_tez_am_container_size : "
- "{2}".format(tez_am_memory_required, llap_concurrency, normalized_tez_am_container_size))
- llap_mem_daemon_size = llap_mem_for_tezAm_and_daemons - tez_am_memory_required
- assert (llap_mem_daemon_size >= yarn_min_container_size), "Calculated 'LLAP Daemon Size = {0}'. Expected >= 'YARN Minimum Container " \
- "Size' ({1})'".format(llap_mem_daemon_size, yarn_min_container_size)
- assert(llap_mem_daemon_size >= mem_per_thread_for_llap or llap_mem_daemon_size >= yarn_min_container_size), "Not enough memory available for executors."
- Logger.info("Calculated 'llap_mem_daemon_size' : {0}, using following : llap_mem_for_tezAm_and_daemons : {1}, tez_am_memory_required : "
- "{2}".format(llap_mem_daemon_size, llap_mem_for_tezAm_and_daemons, tez_am_memory_required))
-
- llap_daemon_mem_per_node = self._normalizeDown(llap_mem_daemon_size / num_llap_nodes_requested, yarn_min_container_size)
- Logger.info("Calculated 'llap_daemon_mem_per_node' : {0}, using following : llap_mem_daemon_size : {1}, num_llap_nodes_requested : {2}, "
- "yarn_min_container_size: {3}".format(llap_daemon_mem_per_node, llap_mem_daemon_size, num_llap_nodes_requested, yarn_min_container_size))
- if (llap_daemon_mem_per_node == 0):
- # Small cluster. No capacity left on a node after running AMs.
- llap_daemon_mem_per_node = mem_per_thread_for_llap
- num_llap_nodes = math.floor(llap_mem_daemon_size / mem_per_thread_for_llap)
- Logger.info("'llap_daemon_mem_per_node' : 0, adjusted 'llap_daemon_mem_per_node' : {0}, 'num_llap_nodes' : {1}, using following: llap_mem_daemon_size : {2}, "
- "mem_per_thread_for_llap : {3}".format(llap_daemon_mem_per_node, num_llap_nodes, llap_mem_daemon_size, mem_per_thread_for_llap))
- elif (llap_daemon_mem_per_node < mem_per_thread_for_llap):
- # Previously computed value of memory per thread may be too high. Cut the number of nodes. (Alternately reduce memory per node)
- llap_daemon_mem_per_node = mem_per_thread_for_llap
- num_llap_nodes = math.floor(llap_mem_daemon_size / mem_per_thread_for_llap)
- Logger.info("'llap_daemon_mem_per_node'({0}) < mem_per_thread_for_llap({1}), adjusted 'llap_daemon_mem_per_node' "
- ": {2}".format(llap_daemon_mem_per_node, mem_per_thread_for_llap, llap_daemon_mem_per_node))
- else:
- # All good. We have a proper value for memoryPerNode.
- num_llap_nodes = num_llap_nodes_requested
- Logger.info("num_llap_nodes : {0}".format(num_llap_nodes))
-
- num_executors_per_node_max = self.get_max_executors_per_node(yarn_nm_mem_in_mb_normalized, cpu_per_nm_host, mem_per_thread_for_llap)
- assert(num_executors_per_node_max >= 1), "Calculated 'Max. Executors per Node' = {0}. Expected values >= 1.".format(num_executors_per_node_max)
- Logger.info("Calculated 'num_executors_per_node_max' : {0}, using following : yarn_nm_mem_in_mb_normalized : {1}, cpu_per_nm_host : {2}, "
- "mem_per_thread_for_llap: {3}".format(num_executors_per_node_max, yarn_nm_mem_in_mb_normalized, cpu_per_nm_host, mem_per_thread_for_llap))
-
- # NumExecutorsPerNode is not necessarily max - since some capacity would have been reserved for AMs, if this value were based on mem.
- num_executors_per_node = min(math.floor(llap_daemon_mem_per_node / mem_per_thread_for_llap), num_executors_per_node_max)
- assert(num_executors_per_node > 0), "Calculated 'Number of Executors Per Node' = {0}. Expected value >= 1".format(num_executors_per_node)
- Logger.info("Calculated 'num_executors_per_node' : {0}, using following : llap_daemon_mem_per_node : {1}, num_executors_per_node_max : {2}, "
- "mem_per_thread_for_llap: {3}".format(num_executors_per_node, llap_daemon_mem_per_node, num_executors_per_node_max, mem_per_thread_for_llap))
-
- # Now figure out how much of the memory will be used by the executors, and how much will be used by the cache.
- total_mem_for_executors_per_node = num_executors_per_node * mem_per_thread_for_llap
- cache_mem_per_node = llap_daemon_mem_per_node - total_mem_for_executors_per_node
-
- tez_runtime_io_sort_mb = ((long)((0.8 * mem_per_thread_for_llap) / 3))
- tez_runtime_unordered_output_buffer_size = long(0.8 * 0.075 * mem_per_thread_for_llap)
- # 'hive_auto_convert_join_noconditionaltask_size' value is in bytes. Thus, multiplying it by 1048576.
- hive_auto_convert_join_noconditionaltask_size = ((long)((0.8 * mem_per_thread_for_llap) / 3)) * MB_TO_BYTES
-
- # Calculate value for prop 'llap_heap_size'
- llap_xmx = max(total_mem_for_executors_per_node * 0.8, total_mem_for_executors_per_node - self.get_llap_headroom_space(services, configurations))
- Logger.info("Calculated llap_app_heap_size : {0}, using following : total_mem_for_executors : {1}".format(llap_xmx, total_mem_for_executors_per_node))
-
- # Calculate 'hive_heapsize' for Hive2/HiveServer2 (HSI)
- hive_server_interactive_heapsize = None
- hive_server_interactive_hosts = self.getHostsWithComponent("HIVE", "HIVE_SERVER_INTERACTIVE", services, hosts)
- if hive_server_interactive_hosts is None:
- # If its None, read the base service YARN's NODEMANAGER node memory, as are host are considered homogenous.
- hive_server_interactive_hosts = self.getHostsWithComponent("YARN", "NODEMANAGER", services, hosts)
- if hive_server_interactive_hosts is not None and len(hive_server_interactive_hosts) > 0:
- host_mem = long(hive_server_interactive_hosts[0]["Hosts"]["total_mem"])
- hive_server_interactive_heapsize = min(max(2048.0, 400.0*llap_concurrency), 3.0/8 * host_mem)
- Logger.info("Calculated 'hive_server_interactive_heapsize' : {0}, using following : llap_concurrency : {1}, host_mem : "
- "{2}".format(hive_server_interactive_heapsize, llap_concurrency, host_mem))
-
-
- Logger.info("Updating the calculations....")
-
- # Done with calculations, updating calculated configs.
-
- normalized_tez_am_container_size = long(normalized_tez_am_container_size)
- putTezInteractiveSiteProperty('tez.am.resource.memory.mb', normalized_tez_am_container_size)
- Logger.info("'Tez for Hive2' config 'tez.am.resource.memory.mb' updated. Current: {0}".format(normalized_tez_am_container_size))
-
- if not llap_concurrency_in_changed_configs:
- min_llap_concurrency = 1
- putHiveInteractiveSiteProperty('hive.server2.tez.sessions.per.default.queue', llap_concurrency)
- putHiveInteractiveSitePropertyAttribute('hive.server2.tez.sessions.per.default.queue', "minimum",
- min_llap_concurrency)
-
- Logger.info("Hive2 config 'hive.server2.tez.sessions.per.default.queue' updated. Min : {0}, Current: {1}" \
- .format(min_llap_concurrency, llap_concurrency))
-
- putHiveInteractiveSitePropertyAttribute('hive.server2.tez.sessions.per.default.queue', "maximum", max_llap_concurreny)
- Logger.info("Hive2 config 'hive.server2.tez.sessions.per.default.queue' updated. Max : {0}".format(max_llap_concurreny))
-
- num_llap_nodes = long(num_llap_nodes)
- putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "minimum", 1)
- putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "maximum", node_manager_cnt)
- if (num_llap_nodes != num_llap_nodes_requested):
- Logger.info("User requested num_llap_nodes : {0}, but used/adjusted value for calculations is : {1}".format(num_llap_nodes_requested, num_llap_nodes))
+ # Adjust capacity scheduler for the 'llap' named queue.
+ self.checkAndManageLlapQueue(services, configurations, hosts, llap_queue_name, llap_named_queue_cap_fraction)
+ hive_tez_am_cap_available = total_llap_mem_normalized
+
+ # Common calculations now, irrespective of the queue selected.
+
+ # Get calculated value for Slider AM container Size
+ slider_am_container_size = self._normalizeUp(self.calculate_slider_am_size(yarn_min_container_size),
+ yarn_min_container_size)
+
+ llap_mem_for_tezAm_and_daemons = total_llap_mem_normalized - slider_am_container_size
+
+ if llap_mem_for_tezAm_and_daemons < 2 * yarn_min_container_size:
+ Logger.warning("Not enough capacity available on the cluster to run LLAP")
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
+
+ # Calculate llap concurrency (i.e. Number of Tez AM's)
+ max_executors_per_node = self.get_max_executors_per_node(yarn_nm_mem_in_mb_normalized, cpu_per_nm_host, mem_per_thread_for_llap)
+
+ # Read 'hive.server2.tez.sessions.per.default.queue' prop if it's in changed-configs, else calculate it.
+ if not llap_concurrency_in_changed_configs:
+ if max_executors_per_node <= 0:
+ Logger.warning("Calculated 'max_executors_per_node' = {0}. Expected value >= 1.".format(max_executors_per_node))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
+
+ # Default 1 AM for every 20 executor threads.
+ # The second part of the min calculates based on mem required for DEFAULT_EXECUTOR_TO_AM_RATIO executors + 1 AM,
+ # making use of total memory. However, it's possible that total memory will not be used - and the numExecutors is
+ # instead limited by #CPUs. Use maxPerNode to factor this in.
+ llap_concurreny_limit = min(math.floor(max_executors_per_node * num_llap_nodes_requested / DEFAULT_EXECUTOR_TO_AM_RATIO), MAX_CONCURRENT_QUERIES)
+ llap_concurrency = min(llap_concurreny_limit, math.floor(llap_mem_for_tezAm_and_daemons / (DEFAULT_EXECUTOR_TO_AM_RATIO * mem_per_thread_for_llap + normalized_tez_am_container_size)))
+ if llap_concurrency == 0:
+ llap_concurrency = 1
+
+ if llap_concurrency * normalized_tez_am_container_size > hive_tez_am_cap_available:
+ llap_concurrency = math.floor(hive_tez_am_cap_available / normalized_tez_am_container_size)
+
+ if llap_concurrency <= 0:
+ Logger.warning("Calculated 'LLAP Concurrent Queries' = {0}. Expected value >= 1.".format(llap_concurrency))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
+ else:
+ # Read current value
+ if 'hive.server2.tez.sessions.per.default.queue' in hsi_site:
+ llap_concurrency = long(hsi_site['hive.server2.tez.sessions.per.default.queue'])
+ if llap_concurrency <= 0:
+ Logger.warning("'hive.server2.tez.sessions.per.default.queue' current value : {0}. Expected value : >= 1".format(llap_concurrency))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
else:
- Logger.info("Used num_llap_nodes for calculations : {0}".format(num_llap_nodes_requested))
- Logger.info("LLAP config 'num_llap_nodes' updated. Min: 1, Max: {0}".format(node_manager_cnt))
+ llap_concurrency = 1
+ Logger.warning("Couldn't retrieve Hive Server interactive's 'hive.server2.tez.sessions.per.default.queue' config. Setting default value 1.")
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
- llap_container_size = long(llap_daemon_mem_per_node)
- putHiveInteractiveSiteProperty('hive.llap.daemon.yarn.container.mb', llap_container_size)
- Logger.info("LLAP config 'hive.llap.daemon.yarn.container.mb' updated. Current: {0}".format(llap_container_size))
+ # Calculate 'Max LLAP Consurrency', irrespective of whether 'llap_concurrency' was read or calculated.
+ max_llap_concurreny_limit = min(math.floor(max_executors_per_node * num_llap_nodes_requested / MIN_EXECUTOR_TO_AM_RATIO), MAX_CONCURRENT_QUERIES)
+ max_llap_concurreny = min(max_llap_concurreny_limit, math.floor(llap_mem_for_tezAm_and_daemons / (MIN_EXECUTOR_TO_AM_RATIO *
+ mem_per_thread_for_llap + normalized_tez_am_container_size)))
+ if max_llap_concurreny == 0:
+ max_llap_concurreny = 1
+
+ if (max_llap_concurreny * normalized_tez_am_container_size) > hive_tez_am_cap_available:
+ max_llap_concurreny = math.floor(hive_tez_am_cap_available / normalized_tez_am_container_size)
+ if max_llap_concurreny <= 0:
+ Logger.warning("Calculated 'Max. LLAP Concurrent Queries' = {0}. Expected value > 1".format(max_llap_concurreny))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
- # Set 'hive.tez.container.size' only if it is read as "SET_ON_FIRST_INVOCATION", implying initialization.
- # Else, we don't (1). Override the previous calculated value or (2). User provided value.
- if self.get_hive_tez_container_size(services) == self.CONFIG_VALUE_UINITIALIZED:
- mem_per_thread_for_llap = long(mem_per_thread_for_llap)
- putHiveInteractiveSiteProperty('hive.tez.container.size', mem_per_thread_for_llap)
- Logger.info("LLAP config 'hive.tez.container.size' updated. Current: {0}".format(mem_per_thread_for_llap))
+ # Calculate value for 'num_llap_nodes', an across cluster config.
+ tez_am_memory_required = llap_concurrency * normalized_tez_am_container_size
+ llap_mem_daemon_size = llap_mem_for_tezAm_and_daemons - tez_am_memory_required
- putTezInteractiveSiteProperty('tez.runtime.io.sort.mb', tez_runtime_io_sort_mb)
- if "tez-site" in services["configurations"] and "tez.runtime.sorter.class" in services["configurations"]["tez-site"]["properties"]:
- if services["configurations"]["tez-site"]["properties"]["tez.runtime.sorter.class"] == "LEGACY":
- putTezInteractiveSiteProperty("tez.runtime.io.sort.mb", "maximum", 1800)
- Logger.info("'Tez for Hive2' config 'tez.runtime.io.sort.mb' updated. Current: {0}".format(tez_runtime_io_sort_mb))
+ if llap_mem_daemon_size < yarn_min_container_size:
+ Logger.warning("Calculated 'LLAP Daemon Size = {0}'. Expected >= 'YARN Minimum Container Size' ({1})'".format(
+ llap_mem_daemon_size, yarn_min_container_size))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
- putTezInteractiveSiteProperty('tez.runtime.unordered.output.buffer.size-mb', tez_runtime_unordered_output_buffer_size)
- Logger.info("'Tez for Hive2' config 'tez.runtime.unordered.output.buffer.size-mb' updated. Current: {0}".format(tez_runtime_unordered_output_buffer_size))
+ if llap_mem_daemon_size < mem_per_thread_for_llap or llap_mem_daemon_size < yarn_min_container_size:
+ Logger.warning("Not enough memory available for executors.")
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
- putHiveInteractiveSiteProperty('hive.auto.convert.join.noconditionaltask.size', hive_auto_convert_join_noconditionaltask_size)
- Logger.info("HIVE2 config 'hive.auto.convert.join.noconditionaltask.size' updated. Current: {0}".format(hive_auto_convert_join_noconditionaltask_size))
+ llap_daemon_mem_per_node = self._normalizeDown(llap_mem_daemon_size / num_llap_nodes_requested, yarn_min_container_size)
+ if llap_daemon_mem_per_node == 0:
+ # Small cluster. No capacity left on a node after running AMs.
+ llap_daemon_mem_per_node = mem_per_thread_for_llap
+ num_llap_nodes = math.floor(llap_mem_daemon_size / mem_per_thread_for_llap)
+ elif llap_daemon_mem_per_node < mem_per_thread_for_llap:
+ # Previously computed value of memory per thread may be too high. Cut the number of nodes. (Alternately reduce memory per node)
+ llap_daemon_mem_per_node = mem_per_thread_for_llap
+ num_llap_nodes = math.floor(llap_mem_daemon_size / mem_per_thread_for_llap)
+ else:
+ # All good. We have a proper value for memoryPerNode.
+ num_llap_nodes = num_llap_nodes_requested
+ num_executors_per_node_max = self.get_max_executors_per_node(yarn_nm_mem_in_mb_normalized, cpu_per_nm_host, mem_per_thread_for_llap)
+ if num_executors_per_node_max < 1:
+ Logger.warning("Calculated 'Max. Executors per Node' = {0}. Expected values >= 1.".format(num_executors_per_node_max))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
- num_executors_per_node = long(num_executors_per_node)
- putHiveInteractiveSiteProperty('hive.llap.daemon.num.executors', num_executors_per_node)
- putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.num.executors', "minimum", 1)
- putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.num.executors', "maximum", int(num_executors_per_node_max))
- Logger.info("LLAP config 'hive.llap.daemon.num.executors' updated. Current: {0}, Min: 1, "
- "Max: {1}".format(num_executors_per_node, int(num_executors_per_node_max)))
- # 'hive.llap.io.threadpool.size' config value is to be set same as value calculated for
- # 'hive.llap.daemon.num.executors' at all times.
- putHiveInteractiveSiteProperty('hive.llap.io.threadpool.size', num_executors_per_node)
- Logger.info("LLAP config 'hive.llap.io.threadpool.size' updated. Current: {0}".format(num_executors_per_node))
+ # NumExecutorsPerNode is not necessarily max - since some capacity would have been reserved for AMs, if this value were based on mem.
+ num_executors_per_node = min(math.floor(llap_daemon_mem_per_node / mem_per_thread_for_llap), num_executors_per_node_max)
+ if num_executors_per_node <= 0:
+ Logger.warning("Calculated 'Number of Executors Per Node' = {0}. Expected value >= 1".format(num_executors_per_node))
+ self.recommendDefaultLlapConfiguration(configurations, services, hosts)
+ return
- cache_mem_per_node = long(cache_mem_per_node)
- putHiveInteractiveSiteProperty('hive.llap.io.memory.size', cache_mem_per_node)
- Logger.info("LLAP config 'hive.llap.io.memory.size' updated. Current: {0}".format(cache_mem_per_node))
- llap_io_enabled = 'false'
- if cache_mem_per_node >= 64:
- llap_io_enabled = 'true'
+ # Now figure out how much of the memory will be used by the executors, and how much will be used by the cache.
+ total_mem_for_executors_per_node = num_executors_per_node * mem_per_thread_for_llap
+ cache_mem_per_node = llap_daemon_mem_per_node - total_mem_for_executors_per_node
- if hive_server_interactive_heapsize != None:
- putHiveInteractiveEnvProperty("hive_heapsize", int(hive_server_interactive_heapsize))
- Logger.info("Hive2 config 'hive_heapsize' updated. Current : {0}".format(int(hive_server_interactive_heapsize)))
+ tez_runtime_io_sort_mb = (long((0.8 * mem_per_thread_for_llap) / 3))
+ tez_runtime_unordered_output_buffer_size = long(0.8 * 0.075 * mem_per_thread_for_llap)
+ # 'hive_auto_convert_join_noconditionaltask_size' value is in bytes. Thus, multiplying it by 1048576.
+ hive_auto_convert_join_noconditionaltask_size = (long((0.8 * mem_per_thread_for_llap) / 3)) * MB_TO_BYTES
- putHiveInteractiveSiteProperty('hive.llap.io.enabled', llap_io_enabled)
- Logger.info("Hive2 config 'hive.llap.io.enabled' updated to '{0}' as part of "
- "'hive.llap.io.memory.size' calculation.".format(llap_io_enabled))
+ # Calculate value for prop 'llap_heap_size'
+ llap_xmx = max(total_mem_for_executors_per_node * 0.8, total_mem_for_executors_per_node - self.get_llap_headroom_space(services, configurations))
- llap_xmx = long(llap_xmx)
- putHiveInteractiveEnvProperty('llap_heap_size', llap_xmx)
- Logger.info("LLAP config 'llap_heap_size' updated. Current: {0}".format(llap_xmx))
+ # Calculate 'hive_heapsize' for Hive2/HiveServer2 (HSI)
+ hive_server_interactive_heapsize = None
+ hive_server_interactive_hosts = self.getHostsWithComponent("HIVE", "HIVE_SERVER_INTERACTIVE", services, hosts)
+ if hive_server_interactive_hosts is None:
+ # If its None, read the base service YARN's NODEMANAGER node memory, as are host are considered homogenous.
+ hive_server_interactive_hosts = self.getHostsWithComponent("YARN", "NODEMANAGER", services, hosts)
+ if hive_server_interactive_hosts is not None and len(hive_server_interactive_hosts) > 0:
+ host_mem = long(hive_server_interactive_hosts[0]["Hosts"]["total_mem"])
+ hive_server_interactive_heapsize = min(max(2048.0, 400.0*llap_concurrency), 3.0/8 * host_mem)
- slider_am_container_size = long(slider_am_container_size)
- putHiveInteractiveEnvProperty('slider_am_container_mb', slider_am_container_size)
- Logger.info("LLAP config 'slider_am_container_mb' updated. Current: {0}".format(slider_am_container_size))
+ # Done with calculations, updating calculated configs.
- except Exception as e:
- # Set default values, if caught an Exception. The 'llap queue capacity' is left untouched, as it can be increased,
- # triggerring recalculation.
- Logger.info(e.message+" Skipping calculating LLAP configs. Setting them to minimum values.")
- traceback.print_exc()
+ normalized_tez_am_container_size = long(normalized_tez_am_container_size)
+ putTezInteractiveSiteProperty('tez.am.resource.memory.mb', normalized_tez_am_container_size)
- try:
- yarn_min_container_size = long(self.get_yarn_min_container_size(services, configurations))
- slider_am_container_size = long(self.calculate_slider_am_size(yarn_min_container_size))
+ if not llap_concurrency_in_changed_configs:
+ min_llap_concurrency = 1
+ putHiveInteractiveSiteProperty('hive.server2.tez.sessions.per.default.queue', llap_concurrency)
+ putHiveInteractiveSitePropertyAttribute('hive.server2.tez.sessions.per.default.queue', "minimum",
+ min_llap_concurrency)
- node_manager_host_list = self.get_node_manager_hosts(services, hosts)
- node_manager_cnt = len(node_manager_host_list)
+ putHiveInteractiveSitePropertyAttribute('hive.server2.tez.sessions.per.default.queue', "maximum", max_llap_concurreny)
- putHiveInteractiveSiteProperty('hive.server2.tez.sessions.per.default.queue', 1)
- putHiveInteractiveSitePropertyAttribute('hive.server2.tez.sessions.per.default.queue', "minimum", 1)
- putHiveInteractiveSitePropertyAttribute('hive.server2.tez.sessions.per.default.queue', "maximum", 1)
+ num_llap_nodes = long(num_llap_nodes)
+ putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "minimum", 1)
+ putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "maximum", node_manager_cnt)
- putHiveInteractiveEnvProperty('num_llap_nodes', 0)
- putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "minimum", 1)
- putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "maximum", node_manager_cnt)
+ llap_container_size = long(llap_daemon_mem_per_node)
+ putHiveInteractiveSiteProperty('hive.llap.daemon.yarn.container.mb', llap_container_size)
- putHiveInteractiveSiteProperty('hive.llap.daemon.yarn.container.mb', yarn_min_container_size)
- putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.yarn.container.mb', "minimum", yarn_min_container_size)
+ # Set 'hive.tez.container.size' only if it is read as "SET_ON_FIRST_INVOCATION", implying initialization.
+ # Else, we don't (1). Override the previous calculated value or (2). User provided value.
+ if self.get_hive_tez_container_size(services) == self.CONFIG_VALUE_UINITIALIZED:
+ mem_per_thread_for_llap = long(mem_per_thread_for_llap)
+ putHiveInteractiveSiteProperty('hive.tez.container.size', mem_per_thread_for_llap)
- putHiveInteractiveSiteProperty('hive.llap.daemon.num.executors', 0)
- putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.num.executors', "minimum", 1)
+ putTezInteractiveSiteProperty('tez.runtime.io.sort.mb', tez_runtime_io_sort_mb)
+ if "tez-site" in services["configurations"] and "tez.runtime.sorter.class" in services["configurations"]["tez-site"]["properties"]:
+ if services["configurations"]["tez-site"]["properties"]["tez.runtime.sorter.class"] == "LEGACY":
+ putTezInteractiveSiteProperty("tez.runtime.io.sort.mb", "maximum", 1800)
- putHiveInteractiveSiteProperty('hive.llap.io.threadpool.size', 0)
+ putTezInteractiveSiteProperty('tez.runtime.unordered.output.buffer.size-mb', tez_runtime_unordered_output_buffer_size)
+ putHiveInteractiveSiteProperty('hive.auto.convert.join.noconditionaltask.size', hive_auto_convert_join_noconditionaltask_size)
- putHiveInteractiveSiteProperty('hive.llap.io.threadpool.size', 0)
+ num_executors_per_node = long(num_executors_per_node)
+ putHiveInteractiveSiteProperty('hive.llap.daemon.num.executors', num_executors_per_node)
+ putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.num.executors', "minimum", 1)
+ putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.num.executors', "maximum", float(num_executors_per_node_max))
- putHiveInteractiveSiteProperty('hive.llap.io.memory.size', 0)
+ # 'hive.llap.io.threadpool.size' config value is to be set same as value calculated for
+ # 'hive.llap.daemon.num.executors' at all times.
+ cache_mem_per_node = long(cache_mem_per_node)
- putHiveInteractiveEnvProperty('llap_heap_size', 0)
+ putHiveInteractiveSiteProperty('hive.llap.io.threadpool.size', num_executors_per_node)
+ putHiveInteractiveSiteProperty('hive.llap.io.memory.size', cache_mem_per_node)
- putHiveInteractiveEnvProperty('slider_am_container_mb', slider_am_container_size)
+ if hive_server_interactive_heapsize is not None:
+ putHiveInteractiveEnvProperty("hive_heapsize", int(hive_server_interactive_heapsize))
- except Exception as e:
- Logger.info("Problem setting minimum values for LLAP configs in Exception code.")
- traceback.print_exc()
+ llap_io_enabled = 'true' if long(cache_mem_per_node) >= 64 else 'false'
+ putHiveInteractiveSiteProperty('hive.llap.io.enabled', llap_io_enabled)
- """
- Checks for the presence of passed-in configuration properties in a given config, if they are changed.
- Reads from services["changed-configurations"].
- Parameters:
- services: Configuration information for the cluster
- config_type : Type of the configuration
- config_names_set : Set of configuration properties to be checked if they are changed.
- all_exists: If True : returns True only if all properties mentioned in 'config_names_set' we found
- in services["changed-configurations"].
- Otherwise, returns False.
- If False : return True, if any of the properties mentioned in config_names_set we found in
- services["changed-configurations"].
- Otherwise, returns False.
- """
- def are_config_props_in_changed_configs(self, services, config_type, config_names_set, all_exists):
+ putHiveInteractiveEnvProperty('llap_heap_size', long(llap_xmx))
+ putHiveInteractiveEnvProperty('slider_am_container_mb', long(slider_am_container_size))
+
+ def recommendDefaultLlapConfiguration(self, configurations, services, hosts):
+ putHiveInteractiveSiteProperty = self.putProperty(configurations, self.HIVE_INTERACTIVE_SITE, services)
+ putHiveInteractiveSitePropertyAttribute = self.putPropertyAttribute(configurations, self.HIVE_INTERACTIVE_SITE)
+
+ putHiveInteractiveEnvProperty = self.putProperty(configurations, "hive-interactive-env", services)
+ putHiveInteractiveEnvPropertyAttribute = self.putPropertyAttribute(configurations, "hive-interactive-env")
+
+ yarn_min_container_size = long(self.get_yarn_min_container_size(services, configurations))
+ slider_am_container_size = long(self.calculate_slider_am_size(yarn_min_container_size))
+
+ node_manager_host_list = self.getHostsForComponent(services, "YARN", "NODEMANAGER")
+ n
<TRUNCATED>