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website/docs/blueprints/data-analytics/_compute_optimized_nodepool.md
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```yaml | ||
# spark-compute-optimized | ||
name: spark-compute-optimized | ||
clusterName: ${module.eks.cluster_name} | ||
ec2NodeClass: | ||
karpenterRole: ${split("/", module.eks_blueprints_addons.karpenter.node_iam_role_arn)[1]} | ||
subnetSelectorTerms: | ||
tags: | ||
Name: "${module.eks.cluster_name}-private*" | ||
securityGroupSelectorTerms: | ||
tags: | ||
Name: ${module.eks.cluster_name}-node | ||
userData: | | ||
MIME-Version: 1.0 | ||
Content-Type: multipart/mixed; boundary="BOUNDARY" | ||
--BOUNDARY | ||
Content-Type: text/x-shellscript; charset="us-ascii" | ||
cat <<-EOF > /etc/profile.d/bootstrap.sh | ||
#!/bin/sh | ||
# Configure the NVMe volumes in RAID0 configuration in the bootstrap.sh call. | ||
# https://github.com/awslabs/amazon-eks-ami/blob/master/files/bootstrap.sh#L35 | ||
# This will create a RAID volume and mount it at /mnt/k8s-disks/0 | ||
# then mount that volume to /var/lib/kubelet, /var/lib/containerd, and /var/log/pods | ||
# this allows the container daemons and pods to write to the RAID0 by default without needing PersistentVolumes | ||
export LOCAL_DISKS='raid0' | ||
EOF | ||
# Source extra environment variables in bootstrap script | ||
sed -i '/^set -o errexit/a\\nsource /etc/profile.d/bootstrap.sh' /etc/eks/bootstrap.sh | ||
--BOUNDARY-- | ||
nodePool: | ||
labels: | ||
- type: karpenter | ||
- NodeGroupType: SparkComputeOptimized | ||
- multiArch: Spark | ||
requirements: | ||
- key: "karpenter.sh/capacity-type" | ||
operator: In | ||
values: ["spot", "on-demand"] | ||
- key: "kubernetes.io/arch" | ||
operator: In | ||
values: ["amd64"] | ||
- key: "karpenter.k8s.aws/instance-category" | ||
operator: In | ||
values: ["c"] | ||
- key: "karpenter.k8s.aws/instance-family" | ||
operator: In | ||
values: ["c5d"] | ||
- key: "karpenter.k8s.aws/instance-cpu" | ||
operator: In | ||
values: ["4", "8", "16", "36"] | ||
- key: "karpenter.k8s.aws/instance-hypervisor" | ||
operator: In | ||
values: ["nitro"] | ||
- key: "karpenter.k8s.aws/instance-generation" | ||
operator: Gt | ||
values: ["2"] | ||
limits: | ||
cpu: 20 # Change this to 1000 or more for production according to your needs | ||
disruption: | ||
consolidationPolicy: WhenEmpty | ||
consolidateAfter: 30s | ||
expireAfter: 720h | ||
weight: 100 | ||
|
||
# spark-graviton-memory-optimized Nodepool | ||
|
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name: spark-graviton-memory-optimized | ||
clusterName: ${module.eks.cluster_name} | ||
ec2NodeClass: | ||
karpenterRole: ${split("/", module.eks_blueprints_addons.karpenter.node_iam_role_arn)[1]} | ||
subnetSelectorTerms: | ||
tags: | ||
Name: "${module.eks.cluster_name}-private*" | ||
securityGroupSelectorTerms: | ||
tags: | ||
Name: ${module.eks.cluster_name}-node | ||
userData: | | ||
MIME-Version: 1.0 | ||
Content-Type: multipart/mixed; boundary="BOUNDARY" | ||
--BOUNDARY | ||
Content-Type: text/x-shellscript; charset="us-ascii" | ||
cat <<-EOF > /etc/profile.d/bootstrap.sh | ||
#!/bin/sh | ||
# Configure the NVMe volumes in RAID0 configuration in the bootstrap.sh call. | ||
# https://github.com/awslabs/amazon-eks-ami/blob/master/files/bootstrap.sh#L35 | ||
# This will create a RAID volume and mount it at /mnt/k8s-disks/0 | ||
# then mount that volume to /var/lib/kubelet, /var/lib/containerd, and /var/log/pods | ||
# this allows the container daemons and pods to write to the RAID0 by default without needing PersistentVolumes | ||
export LOCAL_DISKS='raid0' | ||
EOF | ||
# Source extra environment variables in bootstrap script | ||
sed -i '/^set -o errexit/a\\nsource /etc/profile.d/bootstrap.sh' /etc/eks/bootstrap.sh | ||
--BOUNDARY-- | ||
nodePool: | ||
labels: | ||
- type: karpenter | ||
- NodeGroupType: SparkGravitonMemoryOptimized | ||
- multiArch: Spark | ||
requirements: | ||
- key: "karpenter.sh/capacity-type" | ||
operator: In | ||
values: ["spot", "on-demand"] | ||
- key: "kubernetes.io/arch" | ||
operator: In | ||
values: ["arm64"] | ||
- key: "karpenter.k8s.aws/instance-category" | ||
operator: In | ||
values: ["r"] | ||
- key: "karpenter.k8s.aws/instance-family" | ||
operator: In | ||
values: ["r6gd"] | ||
- key: "karpenter.k8s.aws/instance-cpu" | ||
operator: In | ||
values: ["4", "8", "16", "32"] | ||
- key: "karpenter.k8s.aws/instance-hypervisor" | ||
operator: In | ||
values: ["nitro"] | ||
- key: "karpenter.k8s.aws/instance-generation" | ||
operator: Gt | ||
values: ["2"] | ||
limits: | ||
cpu: 1000 | ||
disruption: | ||
consolidationPolicy: WhenEmpty | ||
consolidateAfter: 30s | ||
expireAfter: 720h | ||
weight: 50 | ||
``` |
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website/docs/blueprints/data-analytics/_replace_s3_bucket_placeholders.mdx
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Once our sample data is uploaded you can run the Spark job. You will need to | ||
replace the *\<S3_BUCKET\>* placeholders in this file with the name of the bucket | ||
created earlier. You can get that value by running `echo $S3_BUCKET`. | ||
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To do this automatically you can run the following, which will create a .old | ||
backup file and do the replacement for you. |
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Run the *taxi-trip-execute.sh* script with the following input. You will use the *S3_BUCKET* variable created earlier. Additionally, you must change YOUR_REGION_HERE with the region of your choice, *us-west-2* for example. | ||
|
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This script will download some example taxi trip data and create duplicates of | ||
it in order to increase the size a bit. This will take a bit of time and will | ||
require a relatively fast internet connection. | ||
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```bash | ||
./taxi-trip-execute.sh ${S3_BUCKET} YOUR_REGION_HERE | ||
``` |
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