47 lines
2.8 KiB
Bash
47 lines
2.8 KiB
Bash
#!/bin/bash
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###http://docs.confluent.io/1.0/kafka-rest/docs/intro.html
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##本脚本解决的需求是：Kafka http-proxy 的测试
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# Get a list of topics
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$ curl "http://localhost:8082/topics"
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[{"name":"test","num_partitions":3},{"name":"test2","num_partitions":1}]
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# Get info about one partition
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$ curl "http://localhost:8082/topics/test"
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{"name":"test","num_partitions":3}
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# Produce a message using binary embedded data with value "Kafka" to the topic test
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$ curl -X POST -H "Content-Type: application/vnd.kafka.binary.v1+json" \
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--data '{"records":[{"value":"S2Fma2E="}]}' "http://localhost:8082/topics/test"
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{"offsets":[{"partition":0,"offset":0,"error_code":null,"error":null}],"key_schema_id":null,"value_schema_id":null}
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# Produce a message using Avro embedded data, including the schema which will
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# be registered with the schema registry and used to validate and serialize
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# before storing the data in Kafka
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$ curl -X POST -H "Content-Type: application/vnd.kafka.avro.v1+json" \
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--data '{"value_schema": "{\"type\": \"record\", \"name\": \"User\", \"fields\": [{\"name\": \"name\", \"type\": \"string\"}]}", "records": [{"value": {"name": "testUser"}}]}' \
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"http://localhost:8082/topics/avrotest"
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{"offsets":[{"partition":0,"offset":0,"error_code":null,"error":null}],"key_schema_id":null,"value_schema_id":21}
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# Create a consumer for binary data, starting at the beginning of the topic's
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# log. Then consume some data from a topic.
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$ curl -X POST -H "Content-Type: application/vnd.kafka.v1+json" \
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--data '{"id": "my_instance", "format": "binary", "auto.offset.reset": "smallest"}' \
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http://localhost:8082/consumers/my_binary_consumer
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{"instance_id":"my_instance","base_uri":"http://localhost:8082/consumers/my_binary_consumer/instances/my_instance"}
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$ curl -X GET -H "Accept: application/vnd.kafka.binary.v1+json" \
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http://localhost:8082/consumers/my_binary_consumer/instances/my_instance/topics/test
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[{"key":null,"value":"S2Fma2E=","partition":0,"offset":0}]
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# Create a consumer for Avro data, starting at the beginning of the topic's
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# log. Then consume some data from a topic, which is decoded, translated to
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# JSON, and included in the response. The schema used for deserialization is
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# fetched automatically from the schema registry.
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$ curl -X POST -H "Content-Type: application/vnd.kafka.v1+json" \
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--data '{"id": "my_instance", "format": "avro", "auto.offset.reset": "smallest"}' \
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http://localhost:8082/consumers/my_avro_consumer
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{"instance_id":"my_instance","base_uri":"http://localhost:8082/consumers/my_avro_consumer/instances/my_instance"}
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$ curl -X GET -H "Accept: application/vnd.kafka.avro.v1+json" \
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http://localhost:8082/consumers/my_avro_consumer/instances/my_instance/topics/avrotest
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[{"key":null,"value":{"name":"testUser"},"partition":0,"offset":0}] |