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融合 S3 连接器

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Amazon S3 Sink Connector 以 Avro ， JSON 或字节格式将数据从 Apache Kafka 主题导出到 S3 对象。Amazon S3 Sink Connector 会定期轮询 Kafka 中的数据，然后将其上传到 S3 。分区程序用于将每个 Kafka 分区的数据拆分为多个区块。每个数据区块都表示为 S3 对象。密钥名称会对主题， Kafka 分区以及此数据块的起始偏移进行编码。

在此设置中，我们将向您展示如何使用 Kafka S3 接收器连接器直接从 Kafka 读取和写入对象存储中的主题。在此测试中，我们使用了独立的 Consfluent 集群，但此设置适用于分布式集群。

  1. 从 Confluent 网站下载 Confluent Kafka 。

  2. 将软件包解压缩到服务器上的文件夹。

  3. 导出两个变量。

    Export CONFLUENT_HOME=/data/confluent/confluent-6.2.0
export PATH=$PATH:/data/confluent/confluent-6.2.0/bin

  4. 对于独立的 Confluent Kafka 设置，集群会在 ` /tmp` 中创建一个临时根文件夹。它还会创建 Zookeeper ， Kafka ，模式注册表， connect ， ksql-server ， 和控制中心文件夹，并从 ` $confuent_home` 复制其各自的配置文件。请参见以下示例：

    root@stlrx2540m1-108:~# ls -ltr /tmp/confluent.406980/
total 28
drwxr-xr-x 4 root root 4096 Oct 29 19:01 zookeeper
drwxr-xr-x 4 root root 4096 Oct 29 19:37 kafka
drwxr-xr-x 4 root root 4096 Oct 29 19:40 schema-registry
drwxr-xr-x 4 root root 4096 Oct 29 19:45 kafka-rest
drwxr-xr-x 4 root root 4096 Oct 29 19:47 connect
drwxr-xr-x 4 root root 4096 Oct 29 19:48 ksql-server
drwxr-xr-x 4 root root 4096 Oct 29 19:53 control-center
root@stlrx2540m1-108:~#

  5. 配置 Zookeeper 。如果使用默认参数，则无需更改任何内容。

    root@stlrx2540m1-108:~# cat  /tmp/confluent.406980/zookeeper/zookeeper.properties  | grep -iv ^#
dataDir=/tmp/confluent.406980/zookeeper/data
clientPort=2181
maxClientCnxns=0
admin.enableServer=false
tickTime=2000
initLimit=5
syncLimit=2
server.179=controlcenter:2888:3888
root@stlrx2540m1-108:~#

    在上述配置中，我们更新了 s服务器。xxx 属性。默认情况下，您需要三个 zookepers 来选择 Kafka 领导者。

  6. 我们在 ` /tmp/confuent.406980/zookeeper /data` 中创建了一个 myid 文件，其唯一 ID 为：

    root@stlrx2540m1-108:~# cat /tmp/confluent.406980/zookeeper/data/myid
179
root@stlrx2540m1-108:~#

    我们使用 myid 文件的最后一个 IP 地址数。我们使用了 Kafka ， connect ， control-center ， Kafka ， Kafka-REST ， ksql-server 和模式注册表配置。

  7. 启动 Kafka 服务。

    root@stlrx2540m1-108:/data/confluent/confluent-6.2.0/bin# confluent local services  start
The local commands are intended for a single-node development environment only,
NOT for production usage.
 
Using CONFLUENT_CURRENT: /tmp/confluent.406980
ZooKeeper is [UP]
Kafka is [UP]
Schema Registry is [UP]
Kafka REST is [UP]
Connect is [UP]
ksqlDB Server is [UP]
Control Center is [UP]
root@stlrx2540m1-108:/data/confluent/confluent-6.2.0/bin#

    每个配置都有一个日志文件夹，可帮助您解决问题。在某些情况下，服务需要较长时间才能启动。确保所有服务均已启动且正在运行。

  8. 使用 Confluent-hub 安装 Kafka 连接。

    root@stlrx2540m1-108:/data/confluent/confluent-6.2.0/bin# ./confluent-hub install confluentinc/kafka-connect-s3:latest
The component can be installed in any of the following Confluent Platform installations:
  1. /data/confluent/confluent-6.2.0 (based on $CONFLUENT_HOME)
  2. /data/confluent/confluent-6.2.0 (where this tool is installed)
Choose one of these to continue the installation (1-2): 1
Do you want to install this into /data/confluent/confluent-6.2.0/share/confluent-hub-components? (yN) y

Component's license:
Confluent Community License
http://www.confluent.io/confluent-community-license
I agree to the software license agreement (yN) y
Downloading component Kafka Connect S3 10.0.3, provided by Confluent, Inc. from Confluent Hub and installing into /data/confluent/confluent-6.2.0/share/confluent-hub-components
Do you want to uninstall existing version 10.0.3? (yN) y
Detected Worker's configs:
  1. Standard: /data/confluent/confluent-6.2.0/etc/kafka/connect-distributed.properties
  2. Standard: /data/confluent/confluent-6.2.0/etc/kafka/connect-standalone.properties
  3. Standard: /data/confluent/confluent-6.2.0/etc/schema-registry/connect-avro-distributed.properties
  4. Standard: /data/confluent/confluent-6.2.0/etc/schema-registry/connect-avro-standalone.properties
  5. Based on CONFLUENT_CURRENT: /tmp/confluent.406980/connect/connect.properties
  6. Used by Connect process with PID 15904: /tmp/confluent.406980/connect/connect.properties
Do you want to update all detected configs? (yN) y
Adding installation directory to plugin path in the following files:
  /data/confluent/confluent-6.2.0/etc/kafka/connect-distributed.properties
  /data/confluent/confluent-6.2.0/etc/kafka/connect-standalone.properties
  /data/confluent/confluent-6.2.0/etc/schema-registry/connect-avro-distributed.properties
  /data/confluent/confluent-6.2.0/etc/schema-registry/connect-avro-standalone.properties
  /tmp/confluent.406980/connect/connect.properties
  /tmp/confluent.406980/connect/connect.properties

Completed
root@stlrx2540m1-108:/data/confluent/confluent-6.2.0/bin#

    您也可以使用 Confluent-hub install conflientint/Kafka-connect-S3 ： 10.0.3 来安装特定版本。

  9. 默认情况下， confuentine-Kafka-connect-S3 安装在 ` /data/confuent/confuent-6.2.0/share/confuent-hub-components/confuentine-Kafka-connect-S3` 中。

  10. 使用新的 Confluentine-Kafka-connect-S3 更新插件路径。

    root@stlrx2540m1-108:~# cat /data/confluent/confluent-6.2.0/etc/kafka/connect-distributed.properties | grep plugin.path
# plugin.path=/usr/local/share/java,/usr/local/share/kafka/plugins,/opt/connectors,
plugin.path=/usr/share/java,/data/zookeeper/confluent/confluent-6.2.0/share/confluent-hub-components,/data/confluent/confluent-6.2.0/share/confluent-hub-components,/data/confluent/confluent-6.2.0/share/confluent-hub-components/confluentinc-kafka-connect-s3
root@stlrx2540m1-108:~#

  11. 停止并重新启动 Consfluent 服务。

    confluent local services  stop
confluent local services  start
root@stlrx2540m1-108:/data/confluent/confluent-6.2.0/bin# confluent local services  status
The local commands are intended for a single-node development environment only,
NOT for production usage.
 
Using CONFLUENT_CURRENT: /tmp/confluent.406980
Connect is [UP]
Control Center is [UP]
Kafka is [UP]
Kafka REST is [UP]
ksqlDB Server is [UP]
Schema Registry is [UP]
ZooKeeper is [UP]
root@stlrx2540m1-108:/data/confluent/confluent-6.2.0/bin#

  12. 在 ` /root/.AWS/credentials` 文件中配置访问 ID 和机密密钥。

    root@stlrx2540m1-108:~# cat /root/.aws/credentials
[default]
aws_access_key_id = xxxxxxxxxxxx
aws_secret_access_key = xxxxxxxxxxxxxxxxxxxxxxxxxx
root@stlrx2540m1-108:~#

  13. 验证存储分段是否可访问。

    root@stlrx2540m4-01:~# aws s3 –endpoint-url http://kafkasgd.rtpppe.netapp.com:10444 ls kafkasgdbucket1-2
2021-10-29 21:04:18       1388 1
2021-10-29 21:04:20       1388 2
2021-10-29 21:04:22       1388 3
root@stlrx2540m4-01:~#

  14. 为 S3 和存储分段配置 S3-sink 属性文件。

    root@stlrx2540m1-108:~# cat /data/confluent/confluent-6.2.0/share/confluent-hub-components/confluentinc-kafka-connect-s3/etc/quickstart-s3.properties | grep -v ^#
name=s3-sink
connector.class=io.confluent.connect.s3.S3SinkConnector
tasks.max=1
topics=s3_testtopic
s3.region=us-west-2
s3.bucket.name=kafkasgdbucket1-2
store.url=http://kafkasgd.rtpppe.netapp.com:10444/
s3.part.size=5242880
flush.size=3
storage.class=io.confluent.connect.s3.storage.S3Storage
format.class=io.confluent.connect.s3.format.avro.AvroFormat
partitioner.class=io.confluent.connect.storage.partitioner.DefaultPartitioner
schema.compatibility=NONE
root@stlrx2540m1-108:~#

  15. 将一些记录导入到 S3 存储分段中。

    kafka-avro-console-producer --broker-list localhost:9092 --topic s3_topic \
--property value.schema='{"type":"record","name":"myrecord","fields":[{"name":"f1","type":"string"}]}'
{"f1": "value1"}
{"f1": "value2"}
{"f1": "value3"}
{"f1": "value4"}
{"f1": "value5"}
{"f1": "value6"}
{"f1": "value7"}
{"f1": "value8"}
{"f1": "value9"}

  16. 加载 S3-sink 连接器。

    root@stlrx2540m1-108:~# confluent local services connect connector load s3-sink  --config /data/confluent/confluent-6.2.0/share/confluent-hub-components/confluentinc-kafka-connect-s3/etc/quickstart-s3.properties
The local commands are intended for a single-node development environment only,
NOT for production usage. https://docs.confluent.io/current/cli/index.html
{
  "name": "s3-sink",
  "config": {
    "connector.class": "io.confluent.connect.s3.S3SinkConnector",
    "flush.size": "3",
    "format.class": "io.confluent.connect.s3.format.avro.AvroFormat",
    "partitioner.class": "io.confluent.connect.storage.partitioner.DefaultPartitioner",
    "s3.bucket.name": "kafkasgdbucket1-2",
    "s3.part.size": "5242880",
    "s3.region": "us-west-2",
    "schema.compatibility": "NONE",
    "storage.class": "io.confluent.connect.s3.storage.S3Storage",
    "store.url": "http://kafkasgd.rtpppe.netapp.com:10444/",
    "tasks.max": "1",
    "topics": "s3_testtopic",
    "name": "s3-sink"
  },
  "tasks": [],
  "type": "sink"
}
root@stlrx2540m1-108:~#

  17. 检查 S3-sink 状态。

    root@stlrx2540m1-108:~# confluent local services connect connector status s3-sink
The local commands are intended for a single-node development environment only,
NOT for production usage. https://docs.confluent.io/current/cli/index.html
{
  "name": "s3-sink",
  "connector": {
    "state": "RUNNING",
    "worker_id": "10.63.150.185:8083"
  },
  "tasks": [
    {
      "id": 0,
      "state": "RUNNING",
      "worker_id": "10.63.150.185:8083"
    }
  ],
  "type": "sink"
}
root@stlrx2540m1-108:~#

  18. 检查日志以确保 S3-sink 已准备好接受主题。

    root@stlrx2540m1-108:~# confluent local services connect log

  19. 查看 Kafka 中的主题。

    kafka-topics --list --bootstrap-server localhost:9092
…
connect-configs
connect-offsets
connect-statuses
default_ksql_processing_log
s3_testtopic
s3_topic
s3_topic_new
root@stlrx2540m1-108:~#

  20. 检查 S3 存储分段中的对象。

    root@stlrx2540m1-108:~# aws s3 --endpoint-url http://kafkasgd.rtpppe.netapp.com:10444 ls --recursive kafkasgdbucket1-2/topics/
2021-10-29 21:24:00        213 topics/s3_testtopic/partition=0/s3_testtopic+0+0000000000.avro
2021-10-29 21:24:00        213 topics/s3_testtopic/partition=0/s3_testtopic+0+0000000003.avro
2021-10-29 21:24:00        213 topics/s3_testtopic/partition=0/s3_testtopic+0+0000000006.avro
2021-10-29 21:24:08        213 topics/s3_testtopic/partition=0/s3_testtopic+0+0000000009.avro
2021-10-29 21:24:08        213 topics/s3_testtopic/partition=0/s3_testtopic+0+0000000012.avro
2021-10-29 21:24:09        213 topics/s3_testtopic/partition=0/s3_testtopic+0+0000000015.avro
root@stlrx2540m1-108:~#

  21. 要验证内容，请运行以下命令将每个文件从 S3 复制到本地文件系统：

    root@stlrx2540m1-108:~# aws s3 --endpoint-url http://kafkasgd.rtpppe.netapp.com:10444 cp s3://kafkasgdbucket1-2/topics/s3_testtopic/partition=0/s3_testtopic+0+0000000000.avro  tes.avro
download: s3://kafkasgdbucket1-2/topics/s3_testtopic/partition=0/s3_testtopic+0+0000000000.avro to ./tes.avro
root@stlrx2540m1-108:~#

  22. 要打印记录，请使用 avro-tools-1.11.0.1.jar （可在中找到 "Apache 归档"）。

    root@stlrx2540m1-108:~# java -jar /usr/src/avro-tools-1.11.0.1.jar tojson tes.avro
21/10/30 00:20:24 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
{"f1":"value1"}
{"f1":"value2"}
{"f1":"value3"}
root@stlrx2540m1-108:~#