#!/bin/bash
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source systemds_cluster.config

# $1 is the instance type
get_memory_and_cores () {
  while IFS="," read -r field1 name memory vCPUs field5 field6
    do
      if [ "$1" = "$name" ]; then
        SPARK_EXECUTOR_MEMORY=$( bc <<< $memory*0.60*1000) #60% of the total memory (beacause of yarn.scheduler.maximum-allocation-mb)
        SPARK_EXECUTOR_CORES=$vCPUs
      fi
    done < aws_ec2_table.csv

}
# $1 key, $2 value
function set_config(){
    sed -i "" "s/\($1 *= *\).*/\1$2/" systemds_cluster.config
}

get_memory_and_cores $INSTANCES_TYPE
SPARK_EXECUTOR_MEMORY="${SPARK_EXECUTOR_MEMORY}MB"
set_config "SPARK_NUM_EXECUTORS" $CORE_INSTANCES_COUNT
set_config "SPARK_EXECUTOR_CORES" $SPARK_EXECUTOR_CORES
set_config "SPARK_EXECUTOR_MEMORY" $SPARK_EXECUTOR_MEMORY
set_config "SPARK_DRIVER_MEMORY" "1G"
set_config "BUCKET" $BUCKET-$(((RANDOM % 999) + 1000))

#Create systemDS bucket
aws s3api create-bucket --bucket $BUCKET --region $REGION &> /dev/null
aws s3api create-bucket --bucket $BUCKET-logs --region $REGION &> /dev/null

# Upload Jar and scripts to s3
aws s3 sync $SYSTEMDS_TARGET_DIRECTORY s3://$BUCKET --exclude "*" --include "*.dml" --include "*config.xml" --include "*DS.jar*"

# Create keypair
if [ ! -f ${KEYPAIR_NAME}.pem ]; then
    aws ec2 create-key-pair --key-name $KEYPAIR_NAME --region $REGION --query "KeyMaterial" --output text > "$KEYPAIR_NAME.pem"
    chmod 700 "${KEYPAIR_NAME}.pem"
    echo "${KEYPAIR_NAME}.pem private key created!"
fi

#Create the cluster
CLUSTER_INFO=$(aws emr create-cluster \
 --applications Name=Ganglia Name=Spark \
 --ec2-attributes '{"KeyName":"'${KEYPAIR_NAME}'",
  "InstanceProfile":"EMR_EC2_DefaultRole"}'\
 --service-role EMR_DefaultRole \
 --enable-debugging \
 --release-label $EMR_VERSION \
 --log-uri "s3://$BUCKET-logs/" \
 --name "SystemDS cluster" \
 --instance-groups '[{"InstanceCount":'${MASTER_INSTANCES_COUNT}',
                        "InstanceGroupType":"MASTER",
                        "InstanceType":"'${INSTANCES_TYPE}'",
                        "Name":"Master Instance Group"},
                      {"InstanceCount":'${CORE_INSTANCES_COUNT}',
                        "InstanceGroupType":"CORE",
                        "InstanceType":"'${INSTANCES_TYPE}'",
                        "Name":"Core Instance Group"}]'\
 --configurations '[{"Classification":"spark","Properties":{"maximizeResourceAllocation": "true"}}]'\
 --scale-down-behavior TERMINATE_AT_TASK_COMPLETION \
 --region $REGION)

CLUSTER_ID=$(echo $CLUSTER_INFO | jq .ClusterId | tr -d '"')
echo "Cluster successfully initialized. Save your ClusterID: "${CLUSTER_ID}
set_config "CLUSTER_ID" $CLUSTER_ID

ip_address=$(curl ipecho.net/plain ; echo)

#Add your ip to the security group
aws ec2 create-security-group --group-name ElasticMapReduce-master --description "info" &> /dev/null
aws ec2 authorize-security-group-ingress \
    --group-name ElasticMapReduce-master \
    --protocol tcp \
    --port 22 \
    --cidr "${ip_address}"/24 &> /dev/null

# Wait for cluster to start
echo "Waiting for cluster running state"
aws emr wait cluster-running --cluster-id $CLUSTER_ID

echo "Cluster info:"
export CLUSTER_URL=$(aws emr describe-cluster --cluster-id $CLUSTER_ID | jq .Cluster.MasterPublicDnsName | tr -d '"')

aws emr ssh --cluster-id $CLUSTER_ID --key-pair-file ${KEYPAIR_NAME}.pem --region $REGION \
    --command 'aws s3 cp s3://system-ds-bucket/target . --recursive --exclude "*" --include "*DS.jar*"'

echo "Spinup finished."
