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From Jark Wu <imj...@gmail.com>
Subject Re: pyflink连接elasticsearch5.4问题
Date Tue, 16 Jun 2020 14:54:58 GMT
Hi,

据我所知,Flink 1.10 官方没有支持Elasticsearch 5.x 版本的 sql connector。

Best,
Jark

On Tue, 16 Jun 2020 at 16:08, Dian Fu <dian0511.fu@gmail.com> wrote:

> 可以发一下完整的异常吗?
>
> 在 2020年6月16日,下午3:45,jack <wslyk606@163.com> 写道:
>
> 连接的版本部分我本地已经修改为 5了,发生了下面的报错;
>
> >>     st_env.connect(
> >>         Elasticsearch()
> >>             .version("5")
> >>             .host("localhost", 9200, "http")
> >>             .index("taxiid-cnts")
> >>             .document_type('taxiidcnt')
> >>             .key_delimiter("$")) \
>
>
>
>
>
>
> 在 2020-06-16 15:38:28,"Dian Fu" <dian0511.fu@gmail.com> 写道:
> >I guess it's because the ES version specified in the job is `6`, however, the jar
used is `5`.
> >
> >> 在 2020年6月16日,下午1:47,jack <wslyk606@163.com> 写道:
> >>
> >> 我这边使用的是pyflink连接es的一个例子,我这边使用的es为5.4.1的版本,pyflink为1.10.1,连接jar包我使用的是
flink-sql-connector-elasticsearch5_2.11-1.10.1.jar,kafka,json的连接包也下载了,连接kafka测试成功了。
> >> 连接es的时候报错,findAndCreateTableSink   failed。
> >> 是不是es的连接jar包原因造成的?哪位遇到过类似问题还请指导一下,感谢。
> >>
> >> Caused by Could not find a suitable  factory for   ‘org.apache.flink.table.factories.TableSinkFactory’
in the classpath.
> >> Reason: Required context properties mismatch
> >>
> >>
> >>
> >> from pyflink.datastream import StreamExecutionEnvironment, TimeCharacteristic
> >> from pyflink.table import StreamTableEnvironment, DataTypes, EnvironmentSettings
> >> from pyflink.table.descriptors import Schema, Kafka, Json, Rowtime, Elasticsearch
> >>
> >>
> >> def area_cnts():
> >>     s_env = StreamExecutionEnvironment.get_execution_environment()
> >>     s_env.set_stream_time_characteristic(TimeCharacteristic.EventTime)
> >>     s_env.set_parallelism(1)
> >>
> >>     # use blink table planner
> >>     st_env = StreamTableEnvironment \
> >>         .create(s_env, environment_settings=EnvironmentSettings
> >>                 .new_instance()
> >>                 .in_streaming_mode()
> >>                 .use_blink_planner().build())
> >>
> >>     # register source and sink
> >>     register_rides_source(st_env)
> >>     register_cnt_sink(st_env)
> >>
> >>     # query
> >>     st_env.from_path("source")\
> >>         .group_by("taxiId")\
> >>         .select("taxiId, count(1) as cnt")\
> >>         .insert_into("sink")
> >>
> >>     # execute
> >>     st_env.execute("6-write_with_elasticsearch")
> >>
> >>
> >> def register_rides_source(st_env):
> >>     st_env \
> >>         .connect(  # declare the external system to connect to
> >>         Kafka()
> >>             .version("universal")
> >>             .topic("Rides")
> >>             .start_from_earliest()
> >>             .property("zookeeper.connect", "zookeeper:2181")
> >>             .property("bootstrap.servers", "kafka:9092")) \
> >>         .with_format(  # declare a format for this system
> >>         Json()
> >>             .fail_on_missing_field(True)
> >>             .schema(DataTypes.ROW([
> >>             DataTypes.FIELD("rideId", DataTypes.BIGINT()),
> >>             DataTypes.FIELD("isStart", DataTypes.BOOLEAN()),
> >>             DataTypes.FIELD("eventTime", DataTypes.TIMESTAMP()),
> >>             DataTypes.FIELD("lon", DataTypes.FLOAT()),
> >>             DataTypes.FIELD("lat", DataTypes.FLOAT()),
> >>             DataTypes.FIELD("psgCnt", DataTypes.INT()),
> >>             DataTypes.FIELD("taxiId", DataTypes.BIGINT())]))) \
> >>         .with_schema(  # declare the schema of the table
> >>         Schema()
> >>             .field("rideId", DataTypes.BIGINT())
> >>             .field("taxiId", DataTypes.BIGINT())
> >>             .field("isStart", DataTypes.BOOLEAN())
> >>             .field("lon", DataTypes.FLOAT())
> >>             .field("lat", DataTypes.FLOAT())
> >>             .field("psgCnt", DataTypes.INT())
> >>             .field("rideTime", DataTypes.TIMESTAMP())
> >>             .rowtime(
> >>             Rowtime()
> >>                 .timestamps_from_field("eventTime")
> >>                 .watermarks_periodic_bounded(60000))) \
> >>         .in_append_mode() \
> >>         .register_table_source("source")
> >>
> >>
> >> def register_cnt_sink(st_env):
> >>     st_env.connect(
> >>         Elasticsearch()
> >>             .version("6")
> >>             .host("elasticsearch", 9200, "http")
> >>             .index("taxiid-cnts")
> >>             .document_type('taxiidcnt')
> >>             .key_delimiter("$")) \
> >>         .with_schema(
> >>             Schema()
> >>                 .field("taxiId", DataTypes.BIGINT())
> >>                 .field("cnt", DataTypes.BIGINT())) \
> >>         .with_format(
> >>            Json()
> >>                .derive_schema()) \
> >>         .in_upsert_mode() \
> >>         .register_table_sink("sink")
> >>
> >>
> >> if __name__ == '__main__':
> >>     area_cnts()
> >>
> >
>
>
>

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