pyspark 在docker上运行气流和Spark，发现错误

4xrmg8kj  于 12个月前  发布在  Spark
关注(0)|答案(1)|浏览(96)

我从bitnami/spark和apache/airflow分别构建spark镜像和airflow。我在使用sparksubmit操作符运行dag spark submit时发现了这个错误。
“/usr/lib/jvm/java-11-openjdk-amd 64/bin/java：没有这样的文件或目录”
结尾是，
“airflow.exceptions.AirflowException：无法执行：spark-submit --master spark：//spark：7077 --executor-memory 1g --driver-memory 1g --name arrow-spark /home/***/scripts/local_to_postgres_pyspark. py。错误代码为：1。”
My Dockerfile.spark：

FROM bitnami/spark:latest

# Install dependencies
USER root
RUN apt-get update && \
    apt-get install -y gcc curl && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Install JBDC Driver
RUN curl -o /opt/bitnami/spark/jars/postgresql-42.6.0.jar https://jdbc.postgresql.org/download/postgresql-42.6.0.jar

COPY ./requirements_for_docker.txt /
RUN pip install -r /requirements_for_docker.txt

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My Dockerfile.airflow：

FROM apache/airflow:2.7.0
USER root

RUN apt-get update && \
    apt-get install -y procps openjdk-11-jre-headless && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*
ENV JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64

# Install dependencies
USER airflow

COPY requirements_for_docker.txt /tmp/requirements_for_docker.txt
RUN pip install --user --upgrade pip
RUN pip install --no-cache-dir --user -r /tmp/requirements_for_docker.txt
RUN pip install apache-airflow-providers-apache-spark==2.1.3

型
我的docker-compose.airflow.yaml文件：

---
version: '3.8'
x-airflow-common:
  &airflow-common
  image: airflow-spark:latest
  # build: .
  environment:
    &airflow-common-env
    AIRFLOW__CORE__EXECUTOR: LocalExecutor
    AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
    AIRFLOW__CORE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
    AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
    AIRFLOW__CORE__LOAD_EXAMPLES: 'false'
    AIRFLOW__API__AUTH_BACKENDS: 'airflow.api.auth.backend.basic_auth,airflow.api.auth.backend.session'
    LD_LIBRARY_PATH: /usr/lib
    AIRFLOW__SCHEDULER__ENABLE_HEALTH_CHECK: 'true'
    _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
    JAVA_HOME: /usr/lib/jvm/java-11-openjdk-amd64
  volumes:
    - ./dags:/opt/airflow/dags
    - ./logs:/opt/airflow/logs
    - ./config:/opt/airflow/config
    - ./plugins:/opt/airflow/plugins
    - ./data_sample:/home/airflow/data_sample
    - ./scripts:/home/airflow/scripts
  user: "${AIRFLOW_UID:-50000}:0"
  depends_on:
    &airflow-common-depends-on
    postgres:
      condition: service_healthy

services:
  postgres:
    image: postgres:13
    environment:
      POSTGRES_USER: airflow
      POSTGRES_PASSWORD: airflow
      POSTGRES_MULTIPLE_DATABASES: "airflow,ownerOfairflow:postgres,ownerOfpostgres"
      MAX_CONNECTIONS: 200
    volumes:
      - postgres-db-volume:/var/lib/postgresql/data
    healthcheck:
      test: ["CMD", "pg_isready", "-U", "airflow"]
      interval: 10s
      retries: 5
      start_period: 5s
    ports:
      - 5432:5432
    restart: always

  pgadmin:
    image: dpage/pgadmin4
    links:
      - postgres
    depends_on:
      - postgres
    restart: always
    ports:
      - "8081:80"
    environment:
      - [email protected]
      - PGADMIN_DEFAULT_PASSWORD=admin
    volumes:
      - ./pgadmin-data:/var/lib/pgadmin

  airflow-webserver:
    <<: *airflow-common
    command: webserver
    ports:
      - "8080:8080"
    healthcheck:
      test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
      interval: 30s
      timeout: 10s
      retries: 5
      start_period: 30s
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

  airflow-scheduler:
    <<: *airflow-common
    command: scheduler
    healthcheck:
      test: ["CMD", "curl", "--fail", "http://localhost:8974/health"]
      interval: 30s
      timeout: 10s
      retries: 5
      start_period: 30s
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

  airflow-init:
    <<: *airflow-common
    entrypoint: /bin/bash
    command:
      - -c
      - |
        function ver() {
          printf "%04d%04d%04d%04d" $${1//./ }
        }
        airflow_version=$$(AIRFLOW__LOGGING__LOGGING_LEVEL=INFO && gosu airflow airflow version)
        airflow_version_comparable=$$(ver $${airflow_version})
        min_airflow_version=2.2.0
        min_airflow_version_comparable=$$(ver $${min_airflow_version})
        if (( airflow_version_comparable < min_airflow_version_comparable )); then
          echo
          echo -e "\033[1;31mERROR!!!: Too old Airflow version $${airflow_version}!\e[0m"
          echo "The minimum Airflow version supported: $${min_airflow_version}. Only use this or higher!"
          echo
          exit 1
        fi
        if [[ -z "${AIRFLOW_UID}" ]]; then
          echo
          echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
          echo "If you are on Linux, you SHOULD follow the instructions below to set "
          echo "AIRFLOW_UID environment variable, otherwise files will be owned by root."
          echo "For other operating systems you can get rid of the warning with manually created .env file:"
          echo "    See: https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#setting-the-right-airflow-user"
          echo
        fi
        one_meg=1048576
        mem_available=$$(($$(getconf _PHYS_PAGES) * $$(getconf PAGE_SIZE) / one_meg))
        cpus_available=$$(grep -cE 'cpu[0-9]+' /proc/stat)
        disk_available=$$(df / | tail -1 | awk '{print $$4}')
        warning_resources="false"
        if (( mem_available < 4000 )) ; then
          echo
          echo -e "\033[1;33mWARNING!!!: Not enough memory available for Docker.\e[0m"
          echo "At least 4GB of memory required. You have $$(numfmt --to iec $$((mem_available * one_meg)))"
          echo
          warning_resources="true"
        fi
        if (( cpus_available < 2 )); then
          echo
          echo -e "\033[1;33mWARNING!!!: Not enough CPUS available for Docker.\e[0m"
          echo "At least 2 CPUs recommended. You have $${cpus_available}"
          echo
          warning_resources="true"
        fi
        if (( disk_available < one_meg * 10 )); then
          echo
          echo -e "\033[1;33mWARNING!!!: Not enough Disk space available for Docker.\e[0m"
          echo "At least 10 GBs recommended. You have $$(numfmt --to iec $$((disk_available * 1024 )))"
          echo
          warning_resources="true"
        fi
        if [[ $${warning_resources} == "true" ]]; then
          echo
          echo -e "\033[1;33mWARNING!!!: You have not enough resources to run Airflow (see above)!\e[0m"
          echo "Please follow the instructions to increase amount of resources available:"
          echo "   https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#before-you-begin"
          echo
        fi
        mkdir -p /sources/logs /sources/dags /sources/plugins
        chown -R "${AIRFLOW_UID}:0" /sources/{logs,dags,plugins}
        exec /entrypoint airflow version
    environment:
      <<: *airflow-common-env
      _AIRFLOW_DB_UPGRADE: 'true'
      _AIRFLOW_WWW_USER_CREATE: 'true'
      _AIRFLOW_WWW_USER_USERNAME: ${_AIRFLOW_WWW_USER_USERNAME:-airflow}
      _AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
      _PIP_ADDITIONAL_REQUIREMENTS: ''
    user: "0:0"
    volumes:
      - ${AIRFLOW_PROJ_DIR:-.}:/sources

volumes:
  postgres-db-volume:

型
我的docker-compose.spark.yaml文件：

version: '2'

services:
  spark:
    image: spark-cluster:latest
    environment:
      - SPARK_MODE=master
      - SPARK_RPC_AUTHENTICATION_ENABLED=no
      - SPARK_RPC_ENCRYPTION_ENABLED=no
      - SPARK_LOCAL_STORAGE_ENCRYPTION_ENABLED=no
      - SPARK_SSL_ENABLED=no
    volumes:
      - ./scripts:/opt/bitnami/spark/scripts
      - ./dags:/opt/bitnami/spark/dags
      - ./data_sample:/opt/bitnami/spark/data_sample
    ports:
      - "8090:8080"
      - "7077:7077"

  spark-worker-1:
    image: spark-cluster:latest
    environment:
      - SPARK_MODE=worker
      - SPARK_MASTER_URL=spark://spark:7077
      - SPARK_WORKER_MEMORY=1G
      - SPARK_WORKER_CORES=1
      - SPARK_RPC_AUTHENTICATION_ENABLED=no
      - SPARK_RPC_ENCRYPTION_ENABLED=no
      - SPARK_LOCAL_STORAGE_ENCRYPTION_ENABLED=no
      - SPARK_SSL_ENABLED=no
    volumes:
      - ./scripts:/opt/bitnami/spark/scripts
      - ./dags:/opt/bitnami/spark/dags
      - ./data_sample:/opt/bitnami/spark/data_sample
  
  spark-worker-2:
    image: spark-cluster:latest
    environment:
      - SPARK_MODE=worker
      - SPARK_MASTER_URL=spark://spark:7077
      - SPARK_WORKER_MEMORY=1G
      - SPARK_WORKER_CORES=1
      - SPARK_RPC_AUTHENTICATION_ENABLED=no
      - SPARK_RPC_ENCRYPTION_ENABLED=no
      - SPARK_LOCAL_STORAGE_ENCRYPTION_ENABLED=no
      - SPARK_SSL_ENABLED=no
    volumes:
      - ./scripts:/opt/bitnami/spark/scripts
      - ./dags:/opt/bitnami/spark/dags
      - ./data_sample:/opt/bitnami/spark/data_sample
    
  spark-worker-3:
    image: spark-cluster:latest
    environment:
      - SPARK_MODE=worker
      - SPARK_MASTER_URL=spark://spark:7077
      - SPARK_WORKER_MEMORY=1G
      - SPARK_WORKER_CORES=1
      - SPARK_RPC_AUTHENTICATION_ENABLED=no
      - SPARK_RPC_ENCRYPTION_ENABLED=no
      - SPARK_LOCAL_STORAGE_ENCRYPTION_ENABLED=no
      - SPARK_SSL_ENABLED=no
    volumes:
      - ./scripts:/opt/bitnami/spark/scripts
      - ./dags:/opt/bitnami/spark/dags
      - ./data_sample:/opt/bitnami/spark/data_sample

  spark-worker-4:
    image: spark-cluster:latest
    environment:
      - SPARK_MODE=worker
      - SPARK_MASTER_URL=spark://spark:7077
      - SPARK_WORKER_MEMORY=1G
      - SPARK_WORKER_CORES=1
      - SPARK_RPC_AUTHENTICATION_ENABLED=no
      - SPARK_RPC_ENCRYPTION_ENABLED=no
      - SPARK_LOCAL_STORAGE_ENCRYPTION_ENABLED=no
      - SPARK_SSL_ENABLED=no
    volumes:
      - ./scripts:/opt/bitnami/spark/scripts
      - ./dags:/opt/bitnami/spark/dags
      - ./data_sample:/opt/bitnami/spark/data_sample
    
  spark-worker-5:
    image: spark-cluster:latest
    environment:
      - SPARK_MODE=worker
      - SPARK_MASTER_URL=spark://spark:7077
      - SPARK_WORKER_MEMORY=1G
      - SPARK_WORKER_CORES=1
      - SPARK_RPC_AUTHENTICATION_ENABLED=no
      - SPARK_RPC_ENCRYPTION_ENABLED=no
      - SPARK_LOCAL_STORAGE_ENCRYPTION_ENABLED=no
      - SPARK_SSL_ENABLED=no
    volumes:
      - ./scripts:/opt/bitnami/spark/scripts
      - ./dags:/opt/bitnami/spark/dags
      - ./data_sample:/opt/bitnami/spark/data_sample
    
  spark-worker-6:
    image: spark-cluster:latest
    environment:
      - SPARK_MODE=worker
      - SPARK_MASTER_URL=spark://spark:7077
      - SPARK_WORKER_MEMORY=1G
      - SPARK_WORKER_CORES=1
      - SPARK_RPC_AUTHENTICATION_ENABLED=no
      - SPARK_RPC_ENCRYPTION_ENABLED=no
      - SPARK_LOCAL_STORAGE_ENCRYPTION_ENABLED=no
      - SPARK_SSL_ENABLED=no
    volumes:
      - ./scripts:/opt/bitnami/spark/scripts
      - ./dags:/opt/bitnami/spark/dags
      - ./data_sample:/opt/bitnami/spark/data_sample

型
我试着加上

ENV JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64

型
从你在我的Dockerfile上看到的。气流

pyspark

1条答案

按热度按时间
xwbd5t1u

xwbd5t1u1#

试着在你的“导出JAVA_HOME”之后添加“导出JAVA_HOME”。
(this是我使用的图像，它可以工作）
同样，如果仍然存在，看看你在spark中使用的python版本和你在气流图像中使用的python版本，在下面的例子中，我不得不改变到python3.11，因为这一点

FROM apache/airflow:2.7.3-python3.11

USER root
RUN apt-get update \
  && apt-get install -y --no-install-recommends \
         openjdk-11-jre-headless \
  && apt-get autoremove -yqq --purge \
  && apt-get clean \
  && rm -rf /var/lib/apt/lists/*
RUN apt update && apt install -y procps
USER airflow
ENV JAVA_HOME=/usr/lib/jvm/java-11-openjdk-arm64
RUN export JAVA_HOME

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