This page shows how to operate Hive on MR3 on Amazon EKS with autoscaling. By following the instruction, the user will learn:
- how to create and configure an EKS cluster for running Hive on MR3 with autoscaling
- how to run Hive on MR3 in the EKS cluster
This scenario has the following prerequisites:
- The user can create an EKS cluster with the command
eksctl
. - The user can create and update IAM policies.
- The user either can create EFS or has access to an S3 bucket for storing transient data.
- The user can configure LoadBalancers.
- A MySQL server for Metastore is running and accessible from the EKS cluster.
- The MySQL server for Metastore is already populated with Hive databases.
- The user has access to an S3 bucket storing the warehouse and all S3 buckets containing datasets.
- The user can download a MySQL connector.
- The user can run Beeline to connect to HiveServer2 running at a particular address.
Although this page is self-contained, we recommend the user to read the page on Autoscaling and the guide on running Hive on MR3 on Amazon EKS before proceeding. Since Amazon EKS is a particular case of Kubernetes, it also helps to try running Hive on MR3 on Minikube as explained in the page On Minikube with a Pre-built Docker Image.
We use a pre-built Docker image mr3project/hivemr3:1.2
available at DockerHub,
so the user does not have to build a new Docker image.
This scenario should take 1 hour to 2 hours to complete, including the time for creating an EKS cluster.
This page has been tested with MR3 release 1.2 and eksctl
0.28.1.
Installation
Download an MR3 release containing the executable scripts.
$ git clone https://github.com/mr3project/mr3-run-k8s.git
$ cd mr3-run-k8s/kubernetes/
$ git reset --hard 3287a3dcda7cdd4875fcc2b5e345bc9089f000dc
Restore those files created for Amazon EKS.
$ mv -f env.sh.eks env.sh
$ mv -f conf/core-site.xml.eks conf/core-site.xml
$ mv -f conf/mr3-site.xml.eks conf/mr3-site.xml
$ mv -f conf/hive-site.xml.eks conf/hive-site.xml
$ mv -f yaml/metastore.yaml.eks yaml/metastore.yaml
$ mv -f yaml/hive.yaml.eks yaml/hive.yaml
$ mv -f yaml/ranger.yaml.eks yaml/ranger.yaml
$ mv -f yaml/ats.yaml.eks yaml/ats.yaml
IAM policy for autoscaling
Create an IAM policy EKSAutoScalingWorkerPolicy
.
{
"Version": "2012-10-17",
"Statement": [
{
"Action": [
"autoscaling:DescribeAutoScalingGroups",
"autoscaling:DescribeAutoScalingInstances",
"autoscaling:DescribeLaunchConfigurations",
"autoscaling:DescribeTags",
"autoscaling:SetDesiredCapacity",
"autoscaling:TerminateInstanceInAutoScalingGroup",
"ec2:DescribeLaunchTemplateVersions"
],
"Resource": "*",
"Effect": "Allow"
}
]
}
Configuring the EKS cluster (eks/cluster.yaml
)
Open eks/cluster.yaml
.
Set the region for an EKS cluster.
$ vi eks/cluster.yaml
metadata:
region: ap-northeast-1
We create an EKS cluster with two node groups: mr3-master
and mr3-worker
.
The mr3-master
node group is intended for HiveServer2, DAGAppMaster, and Metastore Pods,
and uses a single on-demand instance of type m5.xlarge
for the master node.
The mr3-worker
node group is intended for ContainerWorker Pods, and
uses up to three spot instances of type m5d.xlarge
or m5d.2xlarge
for worker nodes.
Note that worker nodes have instance storage.
nodeGroups:
- name: mr3-master
instanceType: m5.xlarge
desiredCapacity: 1
- name: mr3-worker
desiredCapacity: 0
minSize: 0
maxSize: 3
instancesDistribution:
instanceTypes: ["m5d.xlarge", "m5d.2xlarge"]
onDemandBaseCapacity: 0
onDemandPercentageAboveBaseCapacity: 0
spotInstancePools: 1
The following diagram shows an example of the EKS cluster after launch:
In the iam/attachPolicyARNs
field of both node groups mr3-master
and mr3-worker
,
use the ARN (Amazon Resource Name) of the IAM policy created in the previous step.
(Without using the ARN for mr3-master
, the user cannot check the status of the Kubernetes Autoscaler.)
nodeGroups:
- name: mr3-master
iam:
attachPolicyARNs:
- arn:aws:iam::aws:policy/AmazonEKSWorkerNodePolicy
- arn:aws:iam::aws:policy/AmazonEKS_CNI_Policy
- arn:aws:iam::111111111111:policy/EKSAutoScalingWorkerPolicy
- name: mr3-worker
iam:
attachPolicyARNs:
- arn:aws:iam::aws:policy/AmazonEKSWorkerNodePolicy
- arn:aws:iam::aws:policy/AmazonEKS_CNI_Policy
- arn:aws:iam::111111111111:policy/EKSAutoScalingWorkerPolicy
In the preBootstrapCommands
field of the node group mr3-master
,
replace your.server.address
with the address for downloading a MySQL connector jar file
which is necessary for connecting to the MySQL server for Metastore.
In our example, we use mysql-connector-java-8.0.12.jar
.
nodeGroups:
- name: mr3-master
preBootstrapCommands:
- "wget http://your.server.address/mysql-connector-java-8.0.12.jar"
- "mkdir -p /home/ec2-user/lib"
- "mv mysql-connector-java-8.0.12.jar /home/ec2-user/lib"
In the preBootstrapCommands
field of the node group mr3-worker
,
list commands for initializing instance storage.
In our example, we format /dev/nvme1n1
as ext4
and mount a single local disk on the directory /ephemeral1
.
nodeGroups:
- name: mr3-worker
preBootstrapCommands:
- "mkfs -t ext4 /dev/nvme1n1"
- "mkdir -p /ephemeral1"
- "mount /dev/nvme1n1 /ephemeral1"
- "chown ec2-user:ec2-user /ephemeral1"
Creating the EKS cluster
Create an EKS cluster by executing the command eksctl
.
By default, the command eksctl uses all Availability Zones (AZs) from the region specified by the field metadata/region
in eks/cluster.yaml
.
The user should be aware that
Amazon charges for data transfer between different AZs ($0.01/GB to $0.02/GB)
and intermediate data exchanged by ContainerWorkers can cross the AZ boundary.
The user can use a single AZ by updating eks/cluster.yaml
as follows:
$ vi eks/cluster.yaml
availabilityZones: ["ap-northeast-1a", "ap-northeast-1c", "ap-northeast-1d"]
nodeGroups:
- name: mr3-master
availabilityZones: ["ap-northeast-1a"]
- name: mr3-worker
availabilityZones: ["ap-northeast-1a"]
If eksctl
does not accepts this update, upgrade it to the latest version.
Creating an EKS cluster can take 15 minutes or longer.
$ eksctl create cluster -f eks/cluster.yaml
[ℹ] eksctl version 0.28.1
[ℹ] using region ap-northeast-1
[ℹ] subnets for ap-northeast-1a - public:192.168.0.0/19 private:192.168.96.0/19
[ℹ] subnets for ap-northeast-1c - public:192.168.32.0/19 private:192.168.128.0/19
[ℹ] subnets for ap-northeast-1d - public:192.168.64.0/19 private:192.168.160.0/19
...
[✔] EKS cluster "hive-mr3" in "ap-northeast-1" region is ready
The user can find that two Auto Scaling groups are created.
In our example, the mr3-master
node group starts with a single master node
whereas the mr3-worker
node group starts with no node and can attach up to three nodes.
The user can verify that only the master node is available in the EKS cluster.
$ kubectl get nodes
NAME STATUS ROLES AGE VERSION
ip-192-168-18-120.ap-northeast-1.compute.internal Ready <none> 47s v1.14.9-eks-cc7316
The user can get the public IP address of the master node.
$ kubectl describe node ip-192-168-18-120.ap-northeast-1.compute.internal
...
Addresses:
InternalIP: 192.168.18.120
ExternalIP: 18.183.130.42
Hostname: ip-192-168-18-120.ap-northeast-1.compute.internal
InternalDNS: ip-192-168-18-120.ap-northeast-1.compute.internal
ExternalDNS: ec2-18-183-130-42.ap-northeast-1.compute.amazonaws.com
Configuring Kubernetes Autoscaler (eks/cluster-autoscaler-autodiscover.yaml
)
Open eks/cluster-autoscaler-autodiscover.yaml
and change the configuration for autoscaling if necessary.
By default, the Kubernetes Autoscaler removes nodes that stay idle for 1 minute (as specified by --scale-down-unneeded-time
).
$ vi eks/cluster-autoscaler-autodiscover.yaml
spec:
template:
spec:
containers:
command:
- --scale-down-delay-after-add=5m
- --scale-down-unneeded-time=1m
Start the Kubernetes Autoscaler.
$ kubectl apply -f eks/cluster-autoscaler-autodiscover.yaml
serviceaccount/cluster-autoscaler created
clusterrole.rbac.authorization.k8s.io/cluster-autoscaler created
role.rbac.authorization.k8s.io/cluster-autoscaler created
clusterrolebinding.rbac.authorization.k8s.io/cluster-autoscaler created
rolebinding.rbac.authorization.k8s.io/cluster-autoscaler created
deployment.apps/cluster-autoscaler created
The user can check that the Kubernetes Autoscaler has started properly.
$ kubectl logs -f deployment/cluster-autoscaler -n kube-system
...
I1029 06:33:48.128601 1 utils.go:543] Skipping ip-192-168-18-120.ap-northeast-1.compute.internal - no node group config
I1029 06:33:48.128645 1 static_autoscaler.go:393] Scale down status: unneededOnly=true lastScaleUpTime=2020-10-29 06:33:28.110776799 +0000 UTC m=+2.814747604 lastScaleDownDeleteTime=2020-10-29 06:33:28.110776872 +0000 UTC m=+2.814747680 lastScaleDownFailTime=2020-10-29 06:33:28.110776944 +0000 UTC m=+2.814747749 scaleDownForbidden=false isDeleteInProgress=false
Directory for storing transient data
The user can use either EFS or S3 to store transient data. For using EFS, follow the instruction in 1. Creating and mounting EFS below. For using S3, follow the instruction in 2. Using S3 instead of EFS below.
1. Creating and mounting EFS (efs/manifest.yaml
)
The user can create EFS on the AWS Console.
When creating EFS, choose the VPC of the EKS cluster.
Make sure that a mount target is created for each Availability Zone.
If the user can choose the security group for mount targets, use the security group for the EKS cluster
(e.g., eks-cluster-sg-hive-mr3-1259748527
).
Otherwise identify two security groups:
- the security group for the EC2 instances constituting the EKS cluster;
- the security group associated with the EFS mount targets.
If the two security groups are different,
add a rule to allow inbound access using NFS from the first security group so that the EKS cluster can access EFS, as shown below:
Here
sg-096f3c3dff95ad6ae
is the first security group.
Get the file system ID of EFS (e.g., fs-027c9d22
)
and the address (e.g., fs-027c9d22.efs.ap-northeast-1.amazonaws.com
).
Open efs/manifest.yaml
and update the following fields.
$ vi efs/manifest.yaml
data:
file.system.id: fs-027c9d22
aws.region: ap-northeast-1
spec:
template:
spec:
volumes:
- name: pv-volume
nfs:
server: fs-027c9d22.efs.ap-northeast-1.amazonaws.com
If EKS does not accept the use of Deployment objects with apiVersion extensions/v1beta1
,
update efs/manifest.yaml
as follows:
kind: Deployment
apiVersion: apps/v1
spec:
selector:
matchLabels:
app: efs-provisioner
Execute the script mount-efs.sh
to create a PersistentVolume.
$ ./mount-efs.sh
namespace/hivemr3 created
serviceaccount/efs-provisioner created
clusterrole.rbac.authorization.k8s.io/efs-provisioner-runner created
clusterrolebinding.rbac.authorization.k8s.io/run-efs-provisioner created
role.rbac.authorization.k8s.io/leader-locking-efs-provisioner created
rolebinding.rbac.authorization.k8s.io/leader-locking-efs-provisioner created
configmap/efs-provisioner created
deployment.extensions/efs-provisioner created
storageclass.storage.k8s.io/aws-efs created
persistentvolumeclaim/workdir-pvc created
The user can find a new StorageClass aws-efs
, a new Pod, and a new PersistentVolumeClaim (workdir-pvc
).
$ kubectl get sc
NAME PROVISIONER AGE
aws-efs example.com/aws-efs 59s
gp2 (default) kubernetes.io/aws-ebs 36m
$ kubectl get pods -n hivemr3
NAME READY STATUS RESTARTS AGE
efs-provisioner-649ff654ff-msjzb 1/1 Running 0 25s
$ kubectl get pvc -n hivemr3
NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE
workdir-pvc Bound pvc-11c53ae3-19b5-11eb-ad3e-0ead4a1b8916 1Mi RWX aws-efs 39s
2. Using S3 instead of EFS
Set the configuration key hive.exec.scratchdir
in conf/hive-site.xml
to point to the directory on S3 for storing transient data.
Note that we should use prefix s3a
, not s3
.
$ vi conf/hive-site.xml
<property>
<name>hive.exec.scratchdir</name>
<value>s3a://hivemr3-warehouse-dir/workdir/${user.name}</value>
</property>
If necessary,
include an additional inline policy in the IAM roles for the mr3-master
and mr3-worker
node groups
so that every Pod can access the S3 bucket for the scratch directory.
Open env.sh
and set the following two environment variables to empty values.
$ vi env.sh
WORK_DIR_PERSISTENT_VOLUME_CLAIM=
WORK_DIR_PERSISTENT_VOLUME_CLAIM_MOUNT_DIR=
Open yaml/metastore.yaml
and comment out the following lines:
$ vi yaml/metastore.yaml
# - name: work-dir-volume
# mountPath: /opt/mr3-run/work-dir/
# - name: work-dir-volume
# persistentVolumeClaim:
# claimName: workdir-pvc
Open yaml/hive.yaml
and comment out the following lines:
$ vi yaml/hive.yaml
# - name: work-dir-volume
# mountPath: /opt/mr3-run/work-dir
# - name: work-dir-volume
# persistentVolumeClaim:
# claimName: workdir-pvc
Access to the MySQL server for Metastore
Check if the MySQL server for Metastore is accessible from the master node. If the MySQL server is running on Amazon AWS, the user may have to update its security group or VPC configuration.
Configuring Metastore
Open env.sh
and
set the environment variable HIVE_DATABASE_HOST
to the address of the MySQL server for Metastore.
In our example, the MySQL server is running at the IP address 3.112.194.145
.
Set the environment variable HIVE_WAREHOUSE_DIR
to the S3 bucket storing the warehouse.
Note that we should use prefix s3a
, not s3
.
$ vi env.sh
HIVE_DATABASE_HOST=3.112.194.145
HIVE_WAREHOUSE_DIR=s3a://hivemr3-warehouse-dir/warehouse
If the user sets the environment variable HIVE_DATABASE_HOST
to the host name of the MySQL server,
the user should update: 1) the spec/template/spec/hostAliases
field in yaml/metastore.yaml
and yaml/hive.yaml
,
and 2) the configuration key mr3.k8s.host.aliases
in conf/mr3-site.xml
.
Checking configurations for MR3
For conf/core-site.xml
and conf/mr3-site.xml
, the user should use the default values for all configuration keys.
There are three configuration keys that the user may want to update.
-
mr3.k8s.pod.worker.hostpaths
inconf/mr3-site.xml
is set to/ephemeral1
because the instance typesm5d.xlarge
andm5d.2xlarge
for worker nodes are equipped with a single local disk mounted on the directory/ephemeral1
. If the user uses different instance types with multiple local disks, thepreBootstrapCommands
field of the node groupmr3-worker
should be expanded to mount all local disks and the configuration keymr3.k8s.pod.worker.hostpaths
should include additional directories. -
Since the Kubernetes Autoscaler is configured to remove nodes that remain idle for 1 minute for fast scale-in,
mr3.auto.scale.in.grace.period.secs
inconf/mr3-site.xml
is set to 90 seconds (60 seconds of idle time and extra 30 seconds to account for delays). If the user wants to increase the value of--scale-down-unneeded-time
ineks/cluster-autoscaler-autodiscover.yaml
, the configuration keymr3.auto.scale.in.grace.period.secs
should be adjusted accordingly. -
mr3.auto.scale.out.grace.period.secs
inconf/mr3-site.xml
should be set to a sufficiently large value so as to prevent MR3 from prematurely cancelling the provisioning of worker nodes. For example, if it takes about 3 minutes to create and initialize a new worker node,mr3.auto.scale.out.grace.period.secs
can be set to 360 (equivalent to 6 minutes). For more details, see Autoscaling.
Configuring Metastore
Open conf/hive-site.xml
and update configurations for Metastore as necessary.
Below we list some of configuration keys that the user should check.
The two configuration keys javax.jdo.option.ConnectionUserName
and javax.jdo.option.ConnectionPassword
should match
the user name and password of the MySQL server for Metastore.
$ vi conf/hive-site.xml
<property>
<name>hive.metastore.db.type</name>
<value>MYSQL</value>
</property>
<property>
<name>javax.jdo.option.ConnectionDriverName</name>
<value>com.mysql.cj.jdbc.Driver</value>
</property>
<property>
<name>javax.jdo.option.ConnectionUserName</name>
<value>root</value>
</property>
<property>
<name>javax.jdo.option.ConnectionPassword</name>
<value>passwd</value>
</property>
<property>
<name>hive.security.metastore.authenticator.manager</name>
<value>org.apache.hadoop.hive.ql.security.HadoopDefaultMetastoreAuthenticator</value>
</property>
<property>
<name>hive.security.metastore.authorization.manager</name>
<value>org.apache.hadoop.hive.ql.security.authorization.DefaultHiveMetastoreAuthorizationProvider</value>
</property>
<property>
<name>hive.security.authenticator.manager</name>
<value>org.apache.hadoop.hive.ql.security.ProxyUserAuthenticator</value>
</property>
By default, Metastore does not initialize schema.
In order to initialize schema when starting Metastore, update yaml/metastore.yaml
as follows:
$ vi yaml/metastore.yaml
spec:
template:
spec:
containers:
args: ["start", "--kubernetes", "--init-schema"]
Docker image
By default, we use a pre-built Docker image mr3project/hivemr3:1.2
.
If the user wants to use a different Docker image,
check the environment variable DOCKER_HIVE_IMG
in env.sh
and the field spec/template/spec/containers/image
in yaml/metastore.yaml
and yaml/hive.yaml
.
$ vi env.sh
DOCKER_HIVE_IMG=${DOCKER_HIVE_IMG:-mr3project/hive3:1.2}
$ vi yaml/metastore.yaml
spec:
template:
spec:
containers:
- image: mr3project/hive3:1.2
$ vi yaml/hive.yaml
spec:
template:
spec:
containers:
- image: mr3project/hive3:1.2
Accessing S3 buckets
Find the IAM (Identity and Access Management) roles for the mr3-master
and mr3-worker
node groups (which typically look like
eksctl-hive-mr3-nodegroup-mr3-mas-NodeInstanceRole-448MRIYIQ3F8
and eksctl-hive-mr3-nodegroup-mr3-wor-NodeInstanceRole-E19NHT8X0UJ7
).
For both IAM roles,
add the following inline policy or its variant so that every Pod can access S3 buckets storing the warehouse and containing datasets.
Adjust the Action
field to restrict the set of operations permitted to Pods.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"s3:*"
],
"Resource": [
"arn:aws:s3:::hivemr3-warehouse-dir",
"arn:aws:s3:::hivemr3-warehouse-dir/*",
"arn:aws:s3:::hivemr3-partitioned-10-orc",
"arn:aws:s3:::hivemr3-partitioned-10-orc/*"
]
}
]
}
Running Metastore and HiveServer2
Depending on the characteristics of datasets and queries, the user may have to change configurations for Hive on MR3 before running Metastore and HiveServer2. Here are a couple of examples.
- Change resources to be allocated to each mapper, reducer, and ContainerWorker by updating
conf/hive-site.xml
. In particular, the configuration keyshive.mr3.all-in-one.containergroup.memory.mb
andhive.mr3.all-in-one.containergroup.vcores
should be adjusted so that a ContainerWorker can fit in a worker node. For example, we can use the following values for worker nodes of instance typem5d.xlarge
.$ vi conf/hive-site.xml <property> <name>hive.mr3.all-in-one.containergroup.memory.mb</name> <value>15360</value> </property> <property> <name>hive.mr3.all-in-one.containergroup.vcores</name> <value>3</value> </property>
For more details, see Performance Tuning.
- Change the parameters for accessing S3
to avoid
SdkClientException: Unable to execute HTTP request: Timeout waiting for connection from pool
. For more details, see Troubleshooting.
The user can start Metastore by executing the script run-metastore.sh
.
After a Metastore Pod is created,
the user can start HiveServer2 by executing the script run-hive.sh
.
$ ./run-metastore.sh
Error from server (AlreadyExists): namespaces "hivemr3" already exists
...
configmap/client-am-config created
statefulset.apps/hivemr3-metastore created
service/metastore created
$ ./run-hive.sh
...
replicationcontroller/hivemr3-hiveserver2 created
service/hiveserver2 created
HiveServer2 creates a DAGAppMaster Pod. Note, however, that no ContainerWorkers Pods are created until queries are submitted.
$ kubectl get pods -n hivemr3
NAME READY STATUS RESTARTS AGE
efs-provisioner-649ff654ff-msjzb 1/1 Running 0 20m
hivemr3-hiveserver2-wcr5g 1/1 Running 0 89s
hivemr3-metastore-0 1/1 Running 0 102s
mr3master-8561-0-v9fmp 1/1 Running 0 73s
The user can check the log of the DAGAppMaster Pod to make sure that it has started properly.
$ kubectl logs -f -n hivemr3 mr3master-8561-0-v9fmp
...
2020-10-29T08:51:21,059 INFO [DAGAppMaster-1-13] HeartbeatHandler$: Timeout check in HeartbeatHandler:Container
2020-10-29T08:51:21,182 INFO [K8sContainerLauncher-3-1] K8sContainerLauncher: Resynchronizing Pod states for appattempt_8561_0000_000000: 0
Configuring the LoadBalancer
Executing the script run-hive.sh
creates a new LoadBalancer for HiveServer2.
Get the security group associated with the LoadBalancer.
If necessary, edit the inbound rule in order to restrict the source IP addresses (by changing the source from 0.0.0.0/0
to (IP address)/32
.
The LoadBalancer disconnects Beeline showing no activity for the idle timeout period, which is 60 seconds by default. The user may want to increase the idle timeout period, e.g., to 1200 seconds. Otherwise Beeline loses the connection to HiveServer2 even after a brief period of inactivity.
Running Beeline
To run Beeline, get the LoadBalancer Ingress of the Service hiveserver2
.
$ kubectl describe service -n hivemr3 hiveserver2
Name: hiveserver2
Namespace: hivemr3
Labels: <none>
Annotations: <none>
Selector: hivemr3_app=hiveserver2
Type: LoadBalancer
IP: 10.100.134.69
External IPs: 10.1.91.41
LoadBalancer Ingress: aac514ccf19b911ebb0e306616e38843-1372236816.ap-northeast-1.elb.amazonaws.com
...
Get the IP address of the LoadBalancer Ingress.
$ nslookup aac514ccf19b911ebb0e306616e38843-1372236816.ap-northeast-1.elb.amazonaws.com
...
Non-authoritative answer:
Name: aac514ccf19b911ebb0e306616e38843-1372236816.ap-northeast-1.elb.amazonaws.com
Address: 54.168.141.122
Name: aac514ccf19b911ebb0e306616e38843-1372236816.ap-northeast-1.elb.amazonaws.com
Address: 13.115.227.34
In this example, the user can use 54.168.141.122
or 13.115.227.34
as the IP address of HiveServer2 when running Beeline.
This is because Beeline connects first to the LoadBalancer, not directly to HiveServer2.
Here is an example of running Beeline using the address of 13.115.227.34
on another machine where the script hive/run-beeline.sh
is installed.
$ hive/run-beeline.sh --tpcds --hivesrc3
...
Connecting to jdbc:hive2://13.115.227.34:9852/;;
Connected to: Apache Hive (version 3.1.2)
Driver: Hive JDBC (version 3.1.2)
Transaction isolation: TRANSACTION_REPEATABLE_READ
Beeline version 3.1.2 by Apache Hive
0: jdbc:hive2://13.115.227.34:9852/>
After running a few queries, new worker nodes are attached and ContainerWorker Pods are created.
In our example, the EKS cluster ends up with three worker nodes,
consisting of one m5d.2xlarge
instance and two m5d.xlarge
instances.
The last ContainerWorker Pod stays in the state of Pending
because the number of worker nodes has reached its maximum (3 in our example) and no more worker nodes can be attached.
$ kubectl get pods -n hivemr3
NAME READY STATUS RESTARTS AGE
efs-provisioner-649ff654ff-msjzb 1/1 Running 0 42m
hivemr3-hiveserver2-wcr5g 1/1 Running 0 24m
hivemr3-metastore-0 1/1 Running 0 24m
mr3master-8561-0-v9fmp 1/1 Running 0 24m
mr3worker-f2c9-1 1/1 Running 0 21m
mr3worker-f2c9-2 1/1 Running 0 18m
mr3worker-f2c9-3 1/1 Running 0 6m13s
mr3worker-f2c9-4 1/1 Running 0 4m3s
mr3worker-f2c9-5 0/1 Pending 0 2m13s
Here is the progress of scale-out operations:
Here is the progress of scale-in operations:
Note that the EKS cluster does not remove all worker nodes
because the configuration key mr3.auto.scale.in.min.hosts
in mr3-site.xml
is set to 1,
which means that no scale-in operation is performed if the number of worker nodes is 1.
The user can check the progress of autoscaling from the log of the DAGAppMaster Pod.
$ kubectl log -n hivemr3 mr3master-8561-0-v9fmp -f | grep -e Scale -e Scaling -e average
Deleting the EKS cluster
Because of the additional components configured manually,
it take a few extra steps to delete the EKS cluster.
In order to delete the EKS cluster (created with eksctl
), proceed in the following order.
- Remove the new inbound rule (using NFS) in the security group for EFS.
- Delete EFS on the AWS console.
- Remove inline policies from the IAM roles for the
mr3-master
andmr3-worker
node groups. - Execute the command
eksctl delete cluster -f eks/cluster.yaml
.
$ eksctl delete cluster -f eks/cluster.yaml
If the last command fails, the user should delete the EKS cluster manually. Proceed in the following order on the AWS console.
- Delete security groups manually.
- Delete the NAT gateway created for the EKS cluster, delete the VPC, and then delete the Elastic IP address.
- Delete the LoadBalancer.
- Delete IAM roles.
- Delete CloudFormations.