Hive LLAP low Vcore allocation
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Problem Statment:
Hive LLAP Daemons not consuming Cluster VCPU allocation. 80-100 cores available for LLAP daemon, but only using 16.
Summary:
I am testing Hive LLAP on Azure using 2 D14_v2 head nodes, 16 D14_V2 Worker Nodes, and 3 A series Zookeeper nodes. (D14_V2 = 112GB Ram/12vcpu)
The 15 nodes of the 16 node Cluster is dedicated to LLAP
The Distribution is HDP 2.6.3.2-14
Currently the cluster has a total of 1.56TB of Ram Available and 128vcpu. The LLAP Daemons are allocated the proper amount of memory, but the LLAP Daemons only uses 16vcpus total ( 1 vcpu per daemon + 1 vcpu for slider).
Configuration:
My relevant hive configs are as follows:
- hive.llap.daemon.num.executors = 10 (10 of the 12 available vcpu per
node) - Yarn Max Vcores per container - 8
Other:
I have been load testing the cluster but unable to get any more vcpus engaged in the process. Any thoughts or insights would be greatly appreciated.
hive yarn
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up vote
0
down vote
favorite
Problem Statment:
Hive LLAP Daemons not consuming Cluster VCPU allocation. 80-100 cores available for LLAP daemon, but only using 16.
Summary:
I am testing Hive LLAP on Azure using 2 D14_v2 head nodes, 16 D14_V2 Worker Nodes, and 3 A series Zookeeper nodes. (D14_V2 = 112GB Ram/12vcpu)
The 15 nodes of the 16 node Cluster is dedicated to LLAP
The Distribution is HDP 2.6.3.2-14
Currently the cluster has a total of 1.56TB of Ram Available and 128vcpu. The LLAP Daemons are allocated the proper amount of memory, but the LLAP Daemons only uses 16vcpus total ( 1 vcpu per daemon + 1 vcpu for slider).
Configuration:
My relevant hive configs are as follows:
- hive.llap.daemon.num.executors = 10 (10 of the 12 available vcpu per
node) - Yarn Max Vcores per container - 8
Other:
I have been load testing the cluster but unable to get any more vcpus engaged in the process. Any thoughts or insights would be greatly appreciated.
hive yarn
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
Problem Statment:
Hive LLAP Daemons not consuming Cluster VCPU allocation. 80-100 cores available for LLAP daemon, but only using 16.
Summary:
I am testing Hive LLAP on Azure using 2 D14_v2 head nodes, 16 D14_V2 Worker Nodes, and 3 A series Zookeeper nodes. (D14_V2 = 112GB Ram/12vcpu)
The 15 nodes of the 16 node Cluster is dedicated to LLAP
The Distribution is HDP 2.6.3.2-14
Currently the cluster has a total of 1.56TB of Ram Available and 128vcpu. The LLAP Daemons are allocated the proper amount of memory, but the LLAP Daemons only uses 16vcpus total ( 1 vcpu per daemon + 1 vcpu for slider).
Configuration:
My relevant hive configs are as follows:
- hive.llap.daemon.num.executors = 10 (10 of the 12 available vcpu per
node) - Yarn Max Vcores per container - 8
Other:
I have been load testing the cluster but unable to get any more vcpus engaged in the process. Any thoughts or insights would be greatly appreciated.
hive yarn
Problem Statment:
Hive LLAP Daemons not consuming Cluster VCPU allocation. 80-100 cores available for LLAP daemon, but only using 16.
Summary:
I am testing Hive LLAP on Azure using 2 D14_v2 head nodes, 16 D14_V2 Worker Nodes, and 3 A series Zookeeper nodes. (D14_V2 = 112GB Ram/12vcpu)
The 15 nodes of the 16 node Cluster is dedicated to LLAP
The Distribution is HDP 2.6.3.2-14
Currently the cluster has a total of 1.56TB of Ram Available and 128vcpu. The LLAP Daemons are allocated the proper amount of memory, but the LLAP Daemons only uses 16vcpus total ( 1 vcpu per daemon + 1 vcpu for slider).
Configuration:
My relevant hive configs are as follows:
- hive.llap.daemon.num.executors = 10 (10 of the 12 available vcpu per
node) - Yarn Max Vcores per container - 8
Other:
I have been load testing the cluster but unable to get any more vcpus engaged in the process. Any thoughts or insights would be greatly appreciated.
hive yarn
hive yarn
edited Jun 23 at 0:50
asked Jun 22 at 22:26
GregK
3115
3115
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1 Answer
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Resource Manager UI will only show you query co-ordinator and slider's core and memory allocation, each query co-ordinator in LLAP occupy 1 core and mininum alloted Tez-AM memory (tez.am.resource.memory.mb). To check realtime core usage by LLAP service for HDP 2.6.3 version, follow below steps:
Ambari -> Hive -> Quick Links -> Grafana -> Hive LLAP overview ->
Total Execution Slots
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
Resource Manager UI will only show you query co-ordinator and slider's core and memory allocation, each query co-ordinator in LLAP occupy 1 core and mininum alloted Tez-AM memory (tez.am.resource.memory.mb). To check realtime core usage by LLAP service for HDP 2.6.3 version, follow below steps:
Ambari -> Hive -> Quick Links -> Grafana -> Hive LLAP overview ->
Total Execution Slots
add a comment |
up vote
0
down vote
Resource Manager UI will only show you query co-ordinator and slider's core and memory allocation, each query co-ordinator in LLAP occupy 1 core and mininum alloted Tez-AM memory (tez.am.resource.memory.mb). To check realtime core usage by LLAP service for HDP 2.6.3 version, follow below steps:
Ambari -> Hive -> Quick Links -> Grafana -> Hive LLAP overview ->
Total Execution Slots
add a comment |
up vote
0
down vote
up vote
0
down vote
Resource Manager UI will only show you query co-ordinator and slider's core and memory allocation, each query co-ordinator in LLAP occupy 1 core and mininum alloted Tez-AM memory (tez.am.resource.memory.mb). To check realtime core usage by LLAP service for HDP 2.6.3 version, follow below steps:
Ambari -> Hive -> Quick Links -> Grafana -> Hive LLAP overview ->
Total Execution Slots
Resource Manager UI will only show you query co-ordinator and slider's core and memory allocation, each query co-ordinator in LLAP occupy 1 core and mininum alloted Tez-AM memory (tez.am.resource.memory.mb). To check realtime core usage by LLAP service for HDP 2.6.3 version, follow below steps:
Ambari -> Hive -> Quick Links -> Grafana -> Hive LLAP overview ->
Total Execution Slots
answered Nov 11 at 11:25
ShuBham ShaRma
35
35
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add a comment |
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