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From smoha...@apache.org
Subject [2/3] ambari git commit: Revert "AMBARI-19171 Configuring YARN with custom queues leads to misleading errors in Stack Advisor (dgrinenko via dsen)"
Date Fri, 30 Dec 2016 22:15:28 GMT
http://git-wip-us.apache.org/repos/asf/ambari/blob/e97a6e47/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 b52d753..ddf407e 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(
@@ -139,12 +139,14 @@ 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 = self.getSiteProperties(configurations, "application-properties")
+    application_properties = 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))
@@ -181,6 +183,7 @@ 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']:
@@ -249,13 +252,13 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
 
   def validateYarnConfigurations(self, properties, recommendedDefaults, configurations, services, hosts):
     parentValidationProblems = super(HDP25StackAdvisor, self).validateYARNConfigurations(properties, recommendedDefaults, configurations, services, hosts)
-    yarn_site_properties = self.getSiteProperties(configurations, "yarn-site")
+    yarn_site_properties = 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 \
@@ -268,116 +271,124 @@ 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")
-    llap_queue_name = None
-    llap_queue_cap_perc = None
+    hsi_hosts = self.__getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
+    curr_selected_queue_for_llap = None
+    curr_selected_queue_for_llap_cap_perc =  None
     MIN_ASSUMED_CAP_REQUIRED_FOR_SERVICE_CHECKS = 512
-    llap_queue_cap = None
-    hsi_site = self.getServicesSiteProperties(services, self.HIVE_INTERACTIVE_SITE)
-
-    if len(hsi_hosts) == 0:
-      return []
+    current_selected_queue_for_llap_cap =  None
 
-    # 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 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 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 '{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)})
+      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.")
         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))
+          Logger.error("Couldn't retrieve 'hive.llap.daemon.queue.name' config from 'hive-interactive-site' while doing "
+                       "validation checks for Hive Server Interactive.")
+          pass
       else:
-        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)})
+        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)})
 
     validationProblems = self.toConfigurationValidationProblems(validationItems, "hive-interactive-site")
     return validationProblems
 
   def validateHiveInteractiveEnvConfigurations(self, properties, recommendedDefaults, configurations, services, hosts):
-    hive_site_env_properties = self.getSiteProperties(configurations, "hive-interactive-env")
+    hive_site_env_properties = 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[
@@ -385,6 +396,8 @@ 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
@@ -424,15 +437,15 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
 
   def recommendStormConfigurations(self, configurations, clusterData, services, hosts):
     super(HDP25StackAdvisor, self).recommendStormConfigurations(configurations, clusterData, services, hosts)
-    storm_site = self.getServicesSiteProperties(services, "storm-site")
+    storm_site = 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)
@@ -599,7 +612,7 @@ 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 = float(services['configurations']['atlas-env']['properties']['atlas_server_metadata_size'])
+        atlas_server_metadata_size = int(services['configurations']['atlas-env']['properties']['atlas_server_metadata_size'])
 
       atlas_server_xmx = 2048
 
@@ -656,42 +669,47 @@ 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_properties = self.getServicesSiteProperties(services, self.HIVE_INTERACTIVE_SITE)
-
+    hsi_hosts = self.__getHostsForComponent(services, "HIVE", "HIVE_SERVER_INTERACTIVE")
     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 hsi_properties and 'hive.llap.daemon.queue.name' in hsi_properties:
+      if self.HIVE_INTERACTIVE_SITE in services['configurations']:
+        if 'hive.llap.daemon.queue.name' in services['configurations'][self.HIVE_INTERACTIVE_SITE]['properties']:
           self.setLlapDaemonQueuePropAttributes(services, configurations)
 
-          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']
-
+          # 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))
           if hive_tez_default_queue:
             putHiveInteractiveSiteProperty("hive.server2.tez.default.queues", hive_tez_default_queue)
-            Logger.debug("Updated 'hive.server2.tez.default.queues' config : '{0}'".format(hive_tez_default_queue))
+            Logger.info("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 hsi_properties and "hive.llap.zk.sm.connectionString" in hsi_properties:
+    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)
       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 hsi_env_poperties and 'enable_hive_interactive' in hsi_env_poperties:
-      enable_hive_interactive = hsi_env_poperties['enable_hive_interactive']
+    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']
       LLAP_QUEUE_NAME = 'llap'
 
       # Hive Server interactive is already added or getting added
@@ -702,8 +720,8 @@ class HDP25StackAdvisor(HDP24StackAdvisor):
 
     putYarnSiteProperty = self.putProperty(configurations, "yarn-site", services)
     stack_root = "/usr/hdp"
-    if cluster_env and "stack_root" in cluster_env:
-      stack_root = cluster_env["stack_root"]
+    if "cluster-env" in services["configurations"] and "stack_root" in services["configurations"]["cluster-env"]["properties"]:
+      stack_root = services["configurations"]["cluster-env"]["properties"]["stack_root"]
 
     timeline_plugin_classes_values = []
     timeline_plugin_classpath_values = []
@@ -718,457 +736,546 @@ 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))
 
-  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.
+  """
+  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 calculations are in MB, unless specified otherwise.
-    """
+    Note: All memory caluclations are in MB, unless specified otherwise.
+  """
+  def updateLlapConfigs(self, configurations, services, hosts, llap_queue_name):
+    Logger.info("Entered updateLlapConfigs() ..")
     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)
+      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).")
 
-    if hsi_site and "hive.llap.daemon.queue.name" in hsi_site:
-      llap_daemon_selected_queue_name = hsi_site["hive.llap.daemon.queue.name"]
+    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']
 
-    # 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)
+      # 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
         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
-
-      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
+          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))
       else:
-        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)
+        Logger.error("Couldn't retrieve 'capacity-scheduler' properties while doing YARN queue adjustment for Hive Server Interactive."
+                     " Not calculating LLAP configs.")
         return
 
-      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)
+      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"]))
         return
 
-      # 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
+      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:
-        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
-
-    # 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
-
-    # 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
-
-    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
+        # 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))
+      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))
 
-    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
+      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))
 
-    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
+      # 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))
 
-    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
+      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))
 
-    # 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
+      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))
 
-    # 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
+      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))
 
-    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))
+      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))
 
-    # 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)
+      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'
 
-    # Done with calculations, updating calculated configs.
+      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)))
 
-    normalized_tez_am_container_size = long(normalized_tez_am_container_size)
-    putTezInteractiveSiteProperty('tez.am.resource.memory.mb', normalized_tez_am_container_size)
+      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))
 
-    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)
+      llap_xmx = long(llap_xmx)
+      putHiveInteractiveEnvProperty('llap_heap_size', llap_xmx)
+      Logger.info("LLAP config 'llap_heap_size' updated. Current: {0}".format(llap_xmx))
 
-    putHiveInteractiveSitePropertyAttribute('hive.server2.tez.sessions.per.default.queue', "maximum", max_llap_concurreny)
+      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))
 
-    num_llap_nodes = long(num_llap_nodes)
-    putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "minimum", 1)
-    putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "maximum", node_manager_cnt)
+    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()
 
-    llap_container_size = long(llap_daemon_mem_per_node)
-    putHiveInteractiveSiteProperty('hive.llap.daemon.yarn.container.mb', llap_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))
 
-    # 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)
+        node_manager_host_list = self.get_node_manager_hosts(services, hosts)
+        node_manager_cnt = len(node_manager_host_list)
 
-    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.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)
 
-    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)
+        putHiveInteractiveEnvProperty('num_llap_nodes', 0)
+        putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "minimum", 1)
+        putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "maximum", node_manager_cnt)
 
-    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.daemon.yarn.container.mb', yarn_min_container_size)
+        putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.yarn.container.mb', "minimum", yarn_min_container_size)
 
-    # '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)
+        putHiveInteractiveSiteProperty('hive.llap.daemon.num.executors', 0)
+        putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.num.executors', "minimum", 1)
 
-    putHiveInteractiveSiteProperty('hive.llap.io.threadpool.size', num_executors_per_node)
-    putHiveInteractiveSiteProperty('hive.llap.io.memory.size', cache_mem_per_node)
+        putHiveInteractiveSiteProperty('hive.llap.io.threadpool.size', 0)
 
-    if hive_server_interactive_heapsize is not None:
-      putHiveInteractiveEnvProperty("hive_heapsize", int(hive_server_interactive_heapsize))
+        putHiveInteractiveSiteProperty('hive.llap.io.threadpool.size', 0)
 
-    llap_io_enabled = 'true' if long(cache_mem_per_node) >= 64 else 'false'
-    putHiveInteractiveSiteProperty('hive.llap.io.enabled', llap_io_enabled)
+        putHiveInteractiveSiteProperty('hive.llap.io.memory.size', 0)
 
-    putHiveInteractiveEnvProperty('llap_heap_size', long(llap_xmx))
-    putHiveInteractiveEnvProperty('slider_am_container_mb', long(slider_am_container_size))
+        putHiveInteractiveEnvProperty('llap_heap_size', 0)
 
-  def recommendDefaultLlapConfiguration(self, configurations, services, hosts):
-    putHiveInteractiveSiteProperty = self.putProperty(configurations, self.HIVE_INTERACTIVE_SITE, services)
-    putHiveInteractiveSitePropertyAttribute = self.putPropertyAttribute(configurations, self.HIVE_INTERACTIVE_SITE)
+        putHiveInteractiveEnvProperty('slider_am_container_mb', slider_am_container_size)
 
-    putHiveInteractiveEnvProperty = self.putProperty(configurations, "hive-interactive-env", services)
-    putHiveInteractiveEnvPropertyAttribute = self.putPropertyAttribute(configurations, "hive-interactive-env")
+      except Exception as e:
+        Logger.info("Problem setting minimum values for LLAP configs in Exception code.")
+        traceback.print_exc()
 
-    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")
-    node_manager_cnt = len(node_manager_host_list)
-
-    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)
-    putHiveInteractiveEnvProperty('num_llap_nodes', 0)
-    putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "minimum", 1)
-    putHiveInteractiveEnvPropertyAttribute('num_llap_nodes', "maximum", node_manager_cnt)
-    putHiveInteractiveSiteProperty('hive.llap.daemon.yarn.container.mb', yarn_min_container_size)
-    putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.yarn.container.mb', "minimum", yarn_min_container_size)
-    putHiveInteractiveSiteProperty('hive.llap.daemon.num.executors', 0)
-    putHiveInteractiveSitePropertyAttribute('hive.llap.daemon.num.executors

<TRUNCATED>

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