Tracking:
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安装schema register:
该服务用来注册pinot需要的scheme,这样所有需要schema的地方调用该服务即可. http://docs.confluent.io/1.0/installation.html#installation 修改兼容性: curl -X PUT -i -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"compatibility": "FORWARD"}' http://localhost:8801{"compatibility": "FORWARD"} 如何启动: schema-registrybin/schema-registry-start config/schema-registry.properties & 在 schema-registry 服务中创建AvroSchema 1. Register a new version of a schema under the subject "WechatActiveUsersV3" $ curl -X POST -i -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"schema": "{\"type\": \"string\"}"}' http://localhost:8081/subjects/Kafka-key/versions 2. List all subjects $ curl -X GET -i http://localhost:8081/subjects 3. List all schema versions registered under the subject "WechatActiveUsersV3" $ curl -X GET -i http://localhost:8081/subjects/WechatActiveUsersV3/versions 4. Fetch the most recently registered schema under subject "Kafka-value" $ curl -X GET -i http://localhost:8081/subjects/Kafka-value/versions/latest 5. Update compatibility requirements globally $ curl -X PUT -i -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"compatibility": "NONE"}' http://localhost:8081/config 6. Update compatibility requirements under the subject "Kafka-value"$ curl -X PUT -i -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"compatibility": "BACKWARD"}' http://localhost:8081/config/Kafka-value 执行Pinot索引创建 $ gobblin-mapreduce.sh --conf job-conf/WechaActiveUserV3.pull --jars target/parllay-pipeline-gobblin-1.0.0.jar $ hadoop jar /opt/pinot-0.016-pkg/lib/pinot-hadoop-0.016.jar SegmentCreation /path/jobs/WechatActiveUsersV3-Job.properties $ hadoop jar /opt/pinot-0.016-pkg/lib/pinot-hadoop-0.016.jar SegmentTarPush /path/*-Job.properties 创建Pinot对应的Avro元数据 $ curl -X POST -i -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"schema":"{\"namespace\":\"com.parllay.wechat\",\"type\":\"record\",\"name\":\"wechatActiveUserMetrics\",\"fields\":[{\"name\":\"platId\",\"type\":\"string\"},{\"name\":\"openId\",\"type\":\"string\"},{\"name\":\"year\",\"type\":\"int\"},{\"name\":\"month\",\"type\":\"int\"},{\"name\":\"week\",\"type\":\"int\"},{\"name\":\"day\",\"type\":\"int\"},{\"name\":\"hour\",\"type\":\"int\"},{\"name\":\"counter\",\"type\":\"int\"},{\"name\":\"eventTime\",\"type\":\"long\"}]}"}' http://schema.registry:8801/subjects/wechatActiveUserMetrics/versions $ curl -X POST -i -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"schema":"{\"namespace\":\"com.parllay.wechat\",\"type\":\"record\",\"name\":\"wechatEventMetrics\",\"fields\":[{\"name\":\"platId\",\"type\":\"string\"},{\"name\":\"event\",\"type\":\"string\"},{\"name\":\"eventKey\",\"type\":\"string\"},{\"name\":\"eventValue\",\"type\":\"string\"},{\"name\":\"eventKey1\",\"type\":\"string\"},{\"name\":\"eventValue1\",\"type\":\"string\"},{\"name\":\"eventKey2\",\"type\":\"string\"},{\"name\":\"eventValue2\",\"type\":\"string\"},{\"name\":\"countryId\",\"type\":\"int\"},{\"name\":\"provinceId\",\"type\":\"int\"},{\"name\":\"cityId\",\"type\":\"int\"},{\"name\":\"realTimeCountryId\",\"type\":\"int\"},{\"name\":\"realTimeProvinceId\",\"type\":\"int\"},{\"name\":\"realTimeCityId\",\"type\":\"int\"},{\"name\":\"gender\",\"type\":\"int\"},{\"name\":\"groupId\",\"type\":\"int\"},{\"name\":\"languageId\",\"type\":\"int\"},{\"name\":\"tags\",\"type\":{\"type\":\"array\",\"items\":\"int\"}},{\"name\":\"year\",\"type\":\"int\"},{\"name\":\"month\",\"type\":\"int\"},{\"name\":\"week\",\"type\":\"int\"},{\"name\":\"day\",\"type\":\"int\"},{\"name\":\"hour\",\"type\":\"int\"},{\"name\":\"counter\",\"type\":\"int\"},{\"name\":\"eventTime\",\"type\":\"long\"}]}"}' http://schema.registry:8801/subjects/wechatEventMetrics/versions $ curl -X POST -i -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"schema":"{\"namespace\":\"com.parllay.wechat\",\"type\":\"record\",\"name\":\"wechatUserMetrics\",\"fields\":[{\"name\":\"platId\",\"type\":\"string\"},{\"name\":\"openId\",\"type\":\"string\"},{\"name\":\"event\",\"type\":\"string\"},{\"name\":\"eventKey\",\"type\":\"string\"},{\"name\":\"eventValue\",\"type\":\"string\"},{\"name\":\"eventKey1\",\"type\":\"string\"},{\"name\":\"eventValue1\",\"type\":\"string\"},{\"name\":\"eventKey2\",\"type\":\"string\"},{\"name\":\"eventValue2\",\"type\":\"string\"},{\"name\":\"countryId\",\"type\":\"int\"},{\"name\":\"provinceId\",\"type\":\"int\"},{\"name\":\"cityId\",\"type\":\"int\"},{\"name\":\"realTimeCountryId\",\"type\":\"int\"},{\"name\":\"realTimeProvinceId\",\"type\":\"int\"},{\"name\":\"realTimeCityId\",\"type\":\"int\"},{\"name\":\"gender\",\"type\":\"int\"},{\"name\":\"groupId\",\"type\":\"int\"},{\"name\":\"languageId\",\"type\":\"int\"},{\"name\":\"tags\",\"type\":{\"type\":\"array\",\"items\":\"int\"}},{\"name\":\"year\",\"type\":\"int\"},{\"name\":\"month\",\"type\":\"int\"},{\"name\":\"week\",\"type\":\"int\"},{\"name\":\"day\",\"type\":\"int\"},{\"name\":\"hour\",\"type\":\"int\"},{\"name\":\"counter\",\"type\":\"int\"},{\"name\":\"eventTime\",\"type\":\"long\"}]}"}' http://schema.registry:8801/subjects/wechatUserMetrics/versions
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安装hadoop集群:
启动该服务hadoop-2.7.1
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安装spark集群:
启动该服务spark2.0.1
安装azkaban:
启动该服务,详细安装过程参见我的上一篇文章
http://www.jianshu.com/p/fd187cb15674-
编译pinot:
启动controller, broker, server bin/start-server.sh -zkAddress=master:2181 -clusterName=pinot-fht-cluster-v2 -serverHost=slave1 -serverPort=8098 -dataDir=/opt/pinot-0.016-pkg/data -segmentDir=/opt/pinot-0.016-pkg/segment & bin/start-broker.sh -zkAddress=master:2181 -clusterName=pinot-fht-cluster-v2 -brokerHost=slave1 -brokerPort=8099 & bin/start-controller.sh -zkAddress=master:2181 -clusterName=pinot-fht-cluster-v2 -controllerHost=slave1 -controllerPort=9001 -dataDir=/pinot-0.016-pkg/controller &
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编译gobblin:
从kafka导出数据到hdfs, 每次导出都会在zookeeper记录其offset及其wartermark. 每次执行的数据段为上次offset到gobblin启动任务的时间段.
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安装kafka集群
启动集群kafka_2.11-0.9.0.1,创建topic
创建tracking schema, table等
提交schema到schema register服务.
produce数据到kafka集群
测试pinot 数据接收情况. 根据web控制台
生成离线数据.
测试整个数据流程.