stream = t_env.to_append_stream( t_env.from_path('my_source'), Types.ROW([Types.SQL_TIMESTAMP(), Types.STRING(), Types.STRING()])) watermarked_stream = stream.assign_timestamps_and_watermarks( WatermarkStrategy.for_monotonous_timestamps() .with_timestamp_assigner(MyTimestampAssigner())...
t_env = StreamTableEnvironment.create(stream_execution_environment=env) t_env.execute_sql(""" CREATE TABLE my_source ( a INT, b VARCHAR ) WITH ( 'connector' = 'datagen', 'number-of-rows' = '10' ) """) ds = t_env.to_append_stream( t_env.from_path('my_source'), Types.ROW(...
stream = t_env.to_append_stream( t_env.from_path('my_source'), Types.ROW([Types.SQL_TIMESTAMP(), Types.STRING(), Types.STRING()])) watermarked_stream = stream.assign_timestamps_and_watermarks( WatermarkStrategy.for_monotonous_timestamps() .with_timestamp_assigner(MyTimestampAssigner())...
t_env = StreamTableEnvironment.create(stream_execution_environment=env) t_env.execute_sql(""" CREATE TABLE my_source ( a INT, b VARCHAR ) WITH ( 'connector' = 'datagen', 'number-of-rows' = '10' ) """) ds = t_env.to_append_stream( t_env.from_path('my_source'), Types.ROW(...
data = t_env.to_append_stream(result, Types.ROW([Types.FLOAT(), Types.FLOAT()])) data.print() env.execute('stream predict job') 四、完整代码 模型保存代码 model.py importpickleimportpandasaspdfromsklearn.treeimportDecisionTreeClassifier ...
( 'connector' = 'datagen', 'number-of-rows' = '10' ) """) ds = t_env.to_append_stream( t_env.from_path('my_source'), Types.ROW([Types.INT(), Types.STRING()])) def split(s): splits = s[1].split("|") for sp in splits: yield s[0], sp ds = ds.map(lambda i:...
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However, one common use case is to run idempotent queries * (e.g., REPLACE or INSERT OVERWRITE) to upsert into the database and * achieve exactly-once semantic. */ public class ClickHouseTableSink implements AppendStreamTableSink<Row> { private static final Integer BATCH_SIZE_DEFAULT = 5000...
由于DataStream API 本身不支持变更日志处理,因此此方法在stream-to-table 转换期间假定append-only/insert-only 语义。类 Row 的记录必须说明 RowKind.INSERT 更改。 默认情况下,除非明确声明,否则不会传播流记录的时间戳和水印。 此方法允许为结果表声明一个模式。该声明类似于 SQL 中的 {@code CREATE TABLE} DD...
to_append_stream(result).print() # 这里需要修改为实际的表名,并重复32次 2023-11-16 10:22:43 赞同 1 展开评论 打赏 问答分类: 流计算 关系型数据库 MySQL 云数据库 RDS MySQL 版 实时计算 Flink版 问答标签: 实时计算 Flink版CDC 实时计算 Flink版案例 flink数据同步 实时计算 Flink版数据同步 ...