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...@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 <wslyk...@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()
>>
>
