TPC-H with Trusted SparkSQL on Kubernetes¶
Prerequisites¶
Hardware that supports SGX
A fully configured Kubernetes cluster
Intel SGX Device Plugin to use SGX in K8S cluster (install following instructions here)
Prepare TPC-H kit and data¶
Generate data
Go to TPC Download site, choose TPC-H
source code, then download the TPC-H toolkits. Follow the download instructions carefully.
After you download the tpc-h tools zip and uncompressed the zip file. Go to dbgen
directory, and create makefile
based on makefile.suite
, and modify makefile
according to the prompts inside, and run make
.
This should generate an executable called dbgen
./dbgen -h
gives you the various options for generating the tables. The simplest case is running:
./dbgen
which generates tables with extension .tbl
with scale 1 (default) for a total of rougly 1GB size across all tables. For different size tables you can use the -s
option:
./dbgen -s 10
will generate roughly 10GB of input data.
You need to move all .tbl files to a new directory as raw data.
You can then either upload your data to remote file system or read them locally.
Encrypt Data
Encrypt data with specified Key Management Service (SimpleKeyManagementService
, or EHSMKeyManagementService
, or AzureKeyManagementService
). Details can be found here: https://github.com/intel-analytics/BigDL/tree/main/ppml/services/kms-utils/docker
The example code of encrypt data with SimpleKeyManagementService
is like below:
java -cp "$BIGDL_HOME/jars/bigdl-ppml-spark_3.1.2-2.1.0-SNAPSHOT.jar:$SPARK_HOME/conf/:$SPARK_HOME/jars/*:$BIGDL_HOME/jars/*" \
-Xmx10g \
com.intel.analytics.bigdl.ppml.examples.tpch.EncryptFiles \
--inputPath xxx/dbgen-input \
--outputPath xxx/dbgen-encrypted
--kmsType SimpleKeyManagementService
--simpleAPPID xxxxxxxxxxxx \
--simpleAPPKEY xxxxxxxxxxxx \
--primaryKeyPath /path/to/simple_encrypted_primary_key \
--dataKeyPath /path/to/simple_encrypted_data_key
Deploy PPML TPC-H on Kubernetes¶
Pull docker image
sudo docker pull intelanalytics/bigdl-ppml-trusted-big-data-ml-python-graphene:2.1.0-SNAPSHOT
Prepare SGX keys (following instructions here), make sure keys and tpch-spark can be accessed on each K8S node
Start a bigdl-ppml enabled Spark K8S client container with configured local IP, key, tpch and kuberconfig path
export ENCLAVE_KEY=/path/to/enclave-key.pem
export SECURE_PASSWORD_PATH=/path/to/password
export DATA_PATH=/path/to/data
export KEYS_PATH=/path/to/keys
export KUBERCONFIG_PATH=/path/to/kuberconfig
export LOCAL_IP=$local_ip
export DOCKER_IMAGE=intelanalytics/bigdl-ppml-trusted-big-data-ml-python-graphene:2.1.0-SNAPSHOT
sudo docker run -itd \
--privileged \
--net=host \
--name=spark-local-k8s-client \
--oom-kill-disable \
--device=/dev/sgx/enclave \
--device=/dev/sgx/provision \
-v /var/run/aesmd/aesm.socket:/var/run/aesmd/aesm.socket \
-v $SECURE_PASSWORD_PATH:/ppml/trusted-big-data-ml/work/password \
-v $ENCLAVE_KEY:/graphene/Pal/src/host/Linux-SGX/signer/enclave-key.pem \
-v $DATA_PATH:/ppml/trusted-big-data-ml/work/data \
-v $KEYS_PATH:/ppml/trusted-big-data-ml/work/keys \
-v $KUBERCONFIG_PATH:/root/.kube/config \
-e RUNTIME_SPARK_MASTER=k8s://https://$LOCAL_IP:6443 \
-e RUNTIME_K8S_SERVICE_ACCOUNT=spark \
-e RUNTIME_K8S_SPARK_IMAGE=$DOCKER_IMAGE \
-e RUNTIME_DRIVER_HOST=$LOCAL_IP \
-e RUNTIME_DRIVER_PORT=54321 \
-e RUNTIME_EXECUTOR_INSTANCES=1 \
-e RUNTIME_EXECUTOR_CORES=4 \
-e RUNTIME_EXECUTOR_MEMORY=20g \
-e RUNTIME_TOTAL_EXECUTOR_CORES=4 \
-e RUNTIME_DRIVER_CORES=4 \
-e RUNTIME_DRIVER_MEMORY=10g \
-e SGX_MEM_SIZE=64G \
-e SGX_LOG_LEVEL=error \
-e LOCAL_IP=$LOCAL_IP \
$DOCKER_IMAGE bash
Attach to the client container
sudo docker exec -it spark-local-k8s-client bash
Modify
spark-executor-template.yaml
, add path ofenclave-key
,tpch-spark
andkuberconfig
on host
apiVersion: v1
kind: Pod
spec:
containers:
- name: spark-executor
securityContext:
privileged: true
volumeMounts:
...
- name: tpch
mountPath: /ppml/trusted-big-data-ml/work/tpch-spark
- name: kubeconf
mountPath: /root/.kube/config
volumes:
- name: enclave-key
hostPath:
path: /root/keys/enclave-key.pem
...
- name: tpch
hostPath:
path: /path/to/tpch-spark
- name: kubeconf
hostPath:
path: /path/to/kuberconfig
Run PPML TPC-H
secure_password=`openssl rsautl -inkey /ppml/trusted-big-data-ml/work/password/key.txt -decrypt </ppml/trusted-big-data-ml/work/password/output.bin` && \
export TF_MKL_ALLOC_MAX_BYTES=10737418240 && \
export SPARK_LOCAL_IP=$LOCAL_IP && \
export INPUT_DIR=xxx/dbgen-encrypted && \
export OUTPUT_DIR=xxx/dbgen-output && \
/opt/jdk8/bin/java \
-cp '/ppml/trusted-big-data-ml/work/bigdl-2.1.0-SNAPSHOT/lib/bigdl-ppml-spark_3.1.2-2.1.0-SNAPSHOT-jar-with-dependencies.jar:/ppml/trusted-big-data-ml/work/spark-3.1.2/conf/:/ppml/trusted-big-data-ml/work/spark-3.1.2/jars/*' \
-Xmx10g \
-Dbigdl.mklNumThreads=1 \
org.apache.spark.deploy.SparkSubmit \
--master $RUNTIME_SPARK_MASTER \
--deploy-mode client \
--name spark-tpch-sgx \
--conf spark.driver.host=$LOCAL_IP \
--conf spark.driver.port=54321 \
--conf spark.driver.memory=10g \
--conf spark.driver.blockManager.port=10026 \
--conf spark.blockManager.port=10025 \
--conf spark.scheduler.maxRegisteredResourcesWaitingTime=5000000 \
--conf spark.worker.timeout=600 \
--conf spark.python.use.daemon=false \
--conf spark.python.worker.reuse=false \
--conf spark.network.timeout=10000000 \
--conf spark.starvation.timeout=250000 \
--conf spark.rpc.askTimeout=600 \
--conf spark.sql.autoBroadcastJoinThreshold=-1 \
--conf spark.io.compression.codec=lz4 \
--conf spark.sql.shuffle.partitions=8 \
--conf spark.speculation=false \
--conf spark.executor.heartbeatInterval=10000000 \
--conf spark.executor.instances=24 \
--executor-cores 8 \
--total-executor-cores 192 \
--executor-memory 16G \
--properties-file /ppml/trusted-big-data-ml/work/bigdl-2.1.0-SNAPSHOT/conf/spark-bigdl.conf \
--conf spark.kubernetes.authenticate.serviceAccountName=spark \
--conf spark.kubernetes.container.image=$RUNTIME_K8S_SPARK_IMAGE \
--conf spark.kubernetes.executor.podTemplateFile=/ppml/trusted-big-data-ml/spark-executor-template.yaml \
--conf spark.kubernetes.executor.deleteOnTermination=false \
--conf spark.kubernetes.executor.podNamePrefix=spark-tpch-sgx \
--conf spark.kubernetes.sgx.enabled=true \
--conf spark.kubernetes.sgx.executor.mem=32g \
--conf spark.kubernetes.sgx.executor.jvm.mem=10g \
--conf spark.kubernetes.sgx.log.level=$SGX_LOG_LEVEL \
--conf spark.authenticate=true \
--conf spark.authenticate.secret=$secure_password \
--conf spark.kubernetes.executor.secretKeyRef.SPARK_AUTHENTICATE_SECRET="spark-secret:secret" \
--conf spark.kubernetes.driver.secretKeyRef.SPARK_AUTHENTICATE_SECRET="spark-secret:secret" \
--conf spark.authenticate.enableSaslEncryption=true \
--conf spark.network.crypto.enabled=true \
--conf spark.network.crypto.keyLength=128 \
--conf spark.network.crypto.keyFactoryAlgorithm=PBKDF2WithHmacSHA1 \
--conf spark.io.encryption.enabled=true \
--conf spark.io.encryption.keySizeBits=128 \
--conf spark.io.encryption.keygen.algorithm=HmacSHA1 \
--conf spark.ssl.enabled=true \
--conf spark.ssl.port=8043 \
--conf spark.ssl.keyPassword=$secure_password \
--conf spark.ssl.keyStore=/ppml/trusted-big-data-ml/work/keys/keystore.jks \
--conf spark.ssl.keyStorePassword=$secure_password \
--conf spark.ssl.keyStoreType=JKS \
--conf spark.ssl.trustStore=/ppml/trusted-big-data-ml/work/keys/keystore.jks \
--conf spark.ssl.trustStorePassword=$secure_password \
--conf spark.ssl.trustStoreType=JKS \
--conf spark.bigdl.kms.type=SimpleKeyManagementService \
--conf spark.bigdl.kms.simple.id=simpleAPPID \
--conf spark.bigdl.kms.simple.key=simpleAPIKEY \
--conf spark.bigdl.kms.key.primary=xxxx/primaryKey \
--conf spark.bigdl.kms.key.data=xxxx/dataKey \
--class com.intel.analytics.bigdl.ppml.examples.tpch.TpchQuery \
--verbose \
/ppml/trusted-big-data-ml/work/bigdl-2.1.0-SNAPSHOT/lib/bigdl-ppml-spark_3.1.2-2.1.0-SNAPSHOT-jar-with-dependencies.jar \
$INPUT_DIR $OUTPUT_DIR aes/cbc/pkcs5padding plain_text [QUERY]
The optional parameter [QUERY] is the number of the query to run e.g 1, 2, …, 22.
The result is in OUTPUT_DIR. There should be a file called TIMES.TXT with content formatted like:
Q01 39.80204010