Intial version of Kafka container

nigel.stanger / docker-analytics

Browse code Intial version of Kafka container master spark3
1 parent 55a239b commit 60794453326930f800fb846b8f029eae31e728f8 Nigel Stanger authored on 13 May 2019

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all: spark pyspark spark: spark/Dockerfile docker build -t analytics/spark:latest -f $< $@ pyspark: pyspark/Dockerfile docker build -t analytics/pyspark:latest -f $< $@ kafka: kafka/Dockerfile docker build -t analytics/kafka:latest -f $< $@ all: spark pyspark spark: spark/Dockerfile docker build -t analytics/spark:latest -f $< $@ pyspark: pyspark/Dockerfile docker build -t analytics/pyspark:latest -f $< $@

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Makefile

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version: "3.3" services: spark-master: image: analytics/spark:latest container_name: spark-master hostname: spark-master ports: - "8080:8080" - "7077:7077" networks: - spark-network environment: - "SPARK_LOCAL_IP=spark-master" command: "start-master.sh" volumes: - ${HOME}/tmp/sparkdata:/mnt/sparkdata spark-worker: image: analytics/spark:latest depends_on: - spark-master ports: - 8080 networks: - spark-network environment: - "SPARK_MASTER=spark://spark-master:7077" - "SPARK_WORKER_WEBUI_PORT=8080" - "SPARKMONITOR_UI_PORT=8080" command: "start-worker.sh" volumes: - ${HOME}/tmp/sparkdata:/mnt/sparkdata pyspark: image: analytics/pyspark:latest ports: - "8888:8888" networks: - spark-network environment: - "PYSPARK_PYTHON=/usr/local/bin/python3" working_dir: /home/pyspark/work volumes: - ${HOME}/tmp/sparkdata:/mnt/sparkdata kafka: image: analytics/kafka:latest ports: - 9092 networks: - spark-network # environment: # - "PYSPARK_PYTHON=/usr/local/bin/python3" # working_dir: /home/pyspark/work volumes: - ${HOME}/tmp/sparkdata:/mnt/sparkdata networks: spark-network: driver: bridge ipam: driver: default version: "3.3" services: spark-master: image: analytics/spark:latest container_name: spark-master hostname: spark-master ports: - "8080:8080" - "7077:7077" networks: - spark-network environment: - "SPARK_LOCAL_IP=spark-master" command: "start-master.sh" volumes: - ${HOME}/tmp/sparkdata:/mnt/sparkdata spark-worker: image: analytics/spark:latest depends_on: - spark-master ports: - 8080 networks: - spark-network environment: - "SPARK_MASTER=spark://spark-master:7077" - "SPARK_WORKER_WEBUI_PORT=8080" - "SPARKMONITOR_UI_PORT=8080" command: "start-worker.sh" volumes: - ${HOME}/tmp/sparkdata:/mnt/sparkdata pyspark: image: analytics/pyspark:latest ports: - "8888:8888" networks: - spark-network environment: - "PYSPARK_PYTHON=/usr/local/bin/python3" working_dir: /home/pyspark/work volumes: - ${HOME}/tmp/sparkdata:/mnt/sparkdata networks: spark-network: driver: bridge ipam: driver: default

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docker-compose.yml

version: "3.3"
services:
  spark-master:
    image: analytics/spark:latest
    container_name: spark-master
    hostname: spark-master
    ports:
      - "8080:8080"
      - "7077:7077"
    networks:
      - spark-network
    environment:
      - "SPARK_LOCAL_IP=spark-master"
    command: "start-master.sh"
    volumes:
      - ${HOME}/tmp/sparkdata:/mnt/sparkdata
  spark-worker:
    image: analytics/spark:latest
    depends_on:
      - spark-master
    ports:
      - 8080
    networks:
      - spark-network
    environment:
      - "SPARK_MASTER=spark://spark-master:7077"
      - "SPARK_WORKER_WEBUI_PORT=8080"
      - "SPARKMONITOR_UI_PORT=8080"
    command: "start-worker.sh"
    volumes:
      - ${HOME}/tmp/sparkdata:/mnt/sparkdata
  pyspark:
    image: analytics/pyspark:latest
    ports:
      - "8888:8888"
    networks:
      - spark-network
    environment:
      - "PYSPARK_PYTHON=/usr/local/bin/python3"
    working_dir: /home/pyspark/work
    volumes:
      - ${HOME}/tmp/sparkdata:/mnt/sparkdata
  kafka:
    image: analytics/kafka:latest
    ports:
      - 9092
    networks:
      - spark-network
    # environment:
    #   - "PYSPARK_PYTHON=/usr/local/bin/python3"
    # working_dir: /home/pyspark/work
    volumes:
      - ${HOME}/tmp/sparkdata:/mnt/sparkdata
networks:
  spark-network:
    driver: bridge
    ipam:
      driver: default

version: "3.3"
services:
  spark-master:
    image: analytics/spark:latest
    container_name: spark-master
    hostname: spark-master
    ports:
      - "8080:8080"
      - "7077:7077"
    networks:
      - spark-network
    environment:
      - "SPARK_LOCAL_IP=spark-master"
    command: "start-master.sh"
    volumes:
      - ${HOME}/tmp/sparkdata:/mnt/sparkdata
  spark-worker:
    image: analytics/spark:latest
    depends_on:
      - spark-master
    ports:
      - 8080
    networks:
      - spark-network
    environment:
      - "SPARK_MASTER=spark://spark-master:7077"
      - "SPARK_WORKER_WEBUI_PORT=8080"
      - "SPARKMONITOR_UI_PORT=8080"
    command: "start-worker.sh"
    volumes:
      - ${HOME}/tmp/sparkdata:/mnt/sparkdata
  pyspark:
    image: analytics/pyspark:latest
    ports:
      - "8888:8888"
    networks:
      - spark-network
    environment:
      - "PYSPARK_PYTHON=/usr/local/bin/python3"
    working_dir: /home/pyspark/work
    volumes:
      - ${HOME}/tmp/sparkdata:/mnt/sparkdata
networks:
  spark-network:
    driver: bridge
    ipam:
      driver: default

Ignore Space Show notes View kafka/Dockerfile 0 → 100644
FROM analytics/spark ENV KAFKA_VERSION="2.2.0" \ SCALA_VERSION="2.12" \ KAFKA_INSTALL="/usr/local" RUN apk add --no-cache \ bash \ openjdk8 \ tini \ zeromq RUN apk add --no-cache --virtual .fetch-deps \ curl \ tar RUN curl -s https://www-us.apache.org/dist/kafka/$KAFKA_VERSION/kafka_$SCALA_VERSION-$KAFKA_VERSION.tgz \| tar -xz -C $KAFKA_INSTALL && \ cd $KAFKA_INSTALL && ln -s kafka_$SCALA_VERSION-$KAFKA_VERSION kafka RUN apk del .fetch-deps # COPY start-master.sh /usr/local/bin/start-master.sh # COPY start-worker.sh /usr/local/bin/start-worker.sh ENV KAFKA_HOME="$KAFKA_INSTALL/kafka" # SPARK_LOCAL_IP="127.0.0.1" \ # SPARK_MASTER_PORT="7077" \ # SPARK_MASTER_WEBUI_PORT="8080" \ # PYSPARK_PYTHON="/usr/local/bin/python3" COPY start-kafka.sh /usr/local/bin/start-kafka.sh COPY server.properties $KAFKA_HOME/config/server.properties # Spark doesn't seem to respond directly to SIGTERM as the exit status is # for SIGKILL (137), after a pause. Presumably docker-compose down times out. # Using tini gives immediate exit with status 143 (SIGTERM). ENTRYPOINT ["/sbin/tini", "--"] CMD ["/usr/local/bin/start-kafka.sh"]

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kafka/Dockerfile 0 → 100644

FROM analytics/spark

ENV KAFKA_VERSION="2.2.0" \
    SCALA_VERSION="2.12" \
    KAFKA_INSTALL="/usr/local"

RUN apk add --no-cache \
        bash \
        openjdk8 \
        tini \
        zeromq

RUN apk add --no-cache --virtual .fetch-deps \
        curl \
        tar

RUN curl -s https://www-us.apache.org/dist/kafka/$KAFKA_VERSION/kafka_$SCALA_VERSION-$KAFKA_VERSION.tgz | tar -xz -C $KAFKA_INSTALL && \
    cd $KAFKA_INSTALL && ln -s kafka_$SCALA_VERSION-$KAFKA_VERSION kafka

RUN apk del .fetch-deps

# COPY start-master.sh /usr/local/bin/start-master.sh
# COPY start-worker.sh /usr/local/bin/start-worker.sh

ENV KAFKA_HOME="$KAFKA_INSTALL/kafka"
#     SPARK_LOCAL_IP="127.0.0.1" \
#     SPARK_MASTER_PORT="7077" \
#     SPARK_MASTER_WEBUI_PORT="8080" \
#     PYSPARK_PYTHON="/usr/local/bin/python3"
COPY start-kafka.sh /usr/local/bin/start-kafka.sh
COPY server.properties $KAFKA_HOME/config/server.properties

# Spark doesn't seem to respond directly to SIGTERM as the exit status is
# for SIGKILL (137), after a pause. Presumably docker-compose down times out.
# Using tini gives immediate exit with status 143 (SIGTERM).
ENTRYPOINT ["/sbin/tini", "--"]

CMD ["/usr/local/bin/start-kafka.sh"]

Ignore Space Show notes View kafka/server.properties 0 → 100644
# Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # see kafka.server.KafkaConfig for additional details and defaults ############################# Server Basics ############################# # The id of the broker. This must be set to a unique integer for each broker. broker.id=0 ############################# Socket Server Settings ############################# # The address the socket server listens on. It will get the value returned from # java.net.InetAddress.getCanonicalHostName() if not configured. # FORMAT: # listeners = listener_name://host_name:port # EXAMPLE: # listeners = PLAINTEXT://your.host.name:9092 listeners=PLAINTEXT://:9092 # Hostname and port the broker will advertise to producers and consumers. If not set, # it uses the value for "listeners" if configured. Otherwise, it will use the value # returned from java.net.InetAddress.getCanonicalHostName(). #advertised.listeners=PLAINTEXT://your.host.name:9092 # Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details #listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL # The number of threads that the server uses for receiving requests from the network and sending responses to the network num.network.threads=3 # The number of threads that the server uses for processing requests, which may include disk I/O num.io.threads=8 # The send buffer (SO_SNDBUF) used by the socket server socket.send.buffer.bytes=102400 # The receive buffer (SO_RCVBUF) used by the socket server socket.receive.buffer.bytes=102400 # The maximum size of a request that the socket server will accept (protection against OOM) socket.request.max.bytes=104857600 ############################# Log Basics ############################# # A comma separated list of directories under which to store log files log.dirs=/tmp/kafka-logs # The default number of log partitions per topic. More partitions allow greater # parallelism for consumption, but this will also result in more files across # the brokers. num.partitions=1 # The number of threads per data directory to be used for log recovery at startup and flushing at shutdown. # This value is recommended to be increased for installations with data dirs located in RAID array. num.recovery.threads.per.data.dir=1 ############################# Internal Topic Settings ############################# # The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state" # For anything other than development testing, a value greater than 1 is recommended for to ensure availability such as 3. offsets.topic.replication.factor=1 transaction.state.log.replication.factor=1 transaction.state.log.min.isr=1 ############################# Log Flush Policy ############################# # Messages are immediately written to the filesystem but by default we only fsync() to sync # the OS cache lazily. The following configurations control the flush of data to disk. # There are a few important trade-offs here: # 1. Durability: Unflushed data may be lost if you are not using replication. # 2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush. # 3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to excessive seeks. # The settings below allow one to configure the flush policy to flush data after a period of time or # every N messages (or both). This can be done globally and overridden on a per-topic basis. # The number of messages to accept before forcing a flush of data to disk #log.flush.interval.messages=10000 # The maximum amount of time a message can sit in a log before we force a flush #log.flush.interval.ms=1000 ############################# Log Retention Policy ############################# # The following configurations control the disposal of log segments. The policy can # be set to delete segments after a period of time, or after a given size has accumulated. # A segment will be deleted whenever either of these criteria are met. Deletion always happens # from the end of the log. # The minimum age of a log file to be eligible for deletion due to age log.retention.hours=168 # A size-based retention policy for logs. Segments are pruned from the log unless the remaining # segments drop below log.retention.bytes. Functions independently of log.retention.hours. #log.retention.bytes=1073741824 # The maximum size of a log segment file. When this size is reached a new log segment will be created. log.segment.bytes=1073741824 # The interval at which log segments are checked to see if they can be deleted according # to the retention policies log.retention.check.interval.ms=300000 ############################# Zookeeper ############################# # Zookeeper connection string (see zookeeper docs for details). # This is a comma separated host:port pairs, each corresponding to a zk # server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002". # You can also append an optional chroot string to the urls to specify the # root directory for all kafka znodes. zookeeper.connect=localhost:2181 # Timeout in ms for connecting to zookeeper zookeeper.connection.timeout.ms=6000 ############################# Group Coordinator Settings ############################# # The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance. # The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms. # The default value for this is 3 seconds. # We override this to 0 here as it makes for a better out-of-the-box experience for development and testing. # However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup. group.initial.rebalance.delay.ms=0

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kafka/server.properties 0 → 100644

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# see kafka.server.KafkaConfig for additional details and defaults

############################# Server Basics #############################

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0

############################# Socket Server Settings #############################

# The address the socket server listens on. It will get the value returned from 
# java.net.InetAddress.getCanonicalHostName() if not configured.
#   FORMAT:
#     listeners = listener_name://host_name:port
#   EXAMPLE:
#     listeners = PLAINTEXT://your.host.name:9092
listeners=PLAINTEXT://:9092

# Hostname and port the broker will advertise to producers and consumers. If not set, 
# it uses the value for "listeners" if configured.  Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
#advertised.listeners=PLAINTEXT://your.host.name:9092

# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL

# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3

# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=8

# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400

# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400

# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600

############################# Log Basics #############################

# A comma separated list of directories under which to store log files
log.dirs=/tmp/kafka-logs

# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=1

# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.
# This value is recommended to be increased for installations with data dirs located in RAID array.
num.recovery.threads.per.data.dir=1

############################# Internal Topic Settings  #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than 1 is recommended for to ensure availability such as 3.
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1

############################# Log Flush Policy #############################

# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk.
# There are a few important trade-offs here:
#    1. Durability: Unflushed data may be lost if you are not using replication.
#    2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
#    3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to excessive seeks.
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.

# The number of messages to accept before forcing a flush of data to disk
#log.flush.interval.messages=10000

# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=1000

############################# Log Retention Policy #############################

# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.

# The minimum age of a log file to be eligible for deletion due to age
log.retention.hours=168

# A size-based retention policy for logs. Segments are pruned from the log unless the remaining
# segments drop below log.retention.bytes. Functions independently of log.retention.hours.
#log.retention.bytes=1073741824

# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824

# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
log.retention.check.interval.ms=300000

############################# Zookeeper #############################

# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=localhost:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000

############################# Group Coordinator Settings #############################

# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is 3 seconds.
# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=0

Ignore Space Show notes View kafka/start-kafka.sh 0 → 100755
#!/bin/sh $KAFKA_HOME/bin/zookeeper-server-start.sh $KAFKA_HOME/config/zookeeper.properties & $KAFKA_HOME/bin/kafka-server-start.sh $KAFKA_HOME/config/server.properties

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