Hi Godfrey,
Thanks a lot for your response. I just tried it with env.execute("simple
job") but I still get the same error message.
Kant
On Sat, Jan 18, 2020 at 6:26 PM godfrey he <godfre...@gmail.com> wrote:
> hi kant,
>
> > 1) The Documentation says full outer join is supported however the below
> code just exits with value 1. No error message.
> if you have converted Table to DataStream, please execute it
> with StreamExecutionEnvironment ( call env.execute("simple job") )
>
> > 2) If I am using a blink planner should I use TableEnvironment or
> StreamTableEnvironment ?
> for streaming job, both Environment can be used. the difference is:
> TableEnvironment will optimize multiple queries into one DAG when
> executing, while StreamTableEnvironment will independent optimize each
> query.
> StreamTableEnvironment supports convert from/to DataStream,
> while TableEnvironment does not support it.
> StreamTableEnvironment supports register TableFunction
> and AggregateFunction, while TableEnvironment does not support it now.
>
> for batch job, only TableEnvironment is the only choice, because
> DataStream does not support batch job now.
>
> > 3) Why flink current stable documentation(1.9) recommends (old planner)?
> any rough timeline on when we would be able to use blink planner in
> production? perhaps 1.10 or 1.11?
> 1.9 is blink planner's first version, and it is unstable. In 1.10, blink
> planner is more statable, we are switching the blink planner to the default
> step by step [0].
>
> [0]
> http://mail-archives.apache.org/mod_mbox/flink-dev/202001.mbox/%3CCAELO930%2B3RJ5m4hGQ7fbS-CS%3DcfJe5ENcRmZ%3DT_hey-uL6c27g%40mail.gmail.com%3E
>
> kant kodali <kanth...@gmail.com> 于2020年1月18日周六 下午5:40写道：
>
>> Hi All,
>>
>> 1) The Documentation says full outer join is supported however the below
>> code just exits with value 1. No error message.
>>
>> import org.apache.flink.api.common.serialization.SimpleStringSchema;
>> import org.apache.flink.streaming.api.datastream.DataStream;
>> import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
>> import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
>> import org.apache.flink.table.api.*;
>> import org.apache.flink.table.api.java.StreamTableEnvironment;
>> import org.apache.flink.types.Row;
>>
>> import java.util.Properties;
>>
>> public class Test {
>>
>> public static void main(String... args) throws Exception {
>>
>> EnvironmentSettings bsSettings =
>> EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build();
>> final StreamExecutionEnvironment env =
>> StreamExecutionEnvironment.getExecutionEnvironment();
>> StreamTableEnvironment bsTableEnv =
>> StreamTableEnvironment.create(env, bsSettings);
>>
>> Properties properties = new Properties();
>> properties.setProperty("bootstrap.servers", "localhost:9092");
>> properties.setProperty("group.id", "test");
>>
>> FlinkKafkaConsumer<String> consumer1 = new FlinkKafkaConsumer<>(
>> java.util.regex.Pattern.compile("test-topic1"),
>> new SimpleStringSchema(),
>> properties);
>> FlinkKafkaConsumer<String> consumer2 = new FlinkKafkaConsumer<>(
>> java.util.regex.Pattern.compile("test-topic2"),
>> new SimpleStringSchema(),
>> properties);
>>
>> DataStream<String> stream1 = env.addSource(consumer1);
>> DataStream<String> stream2 = env.addSource(consumer2);
>>
>> bsTableEnv.registerDataStream("sample1", stream1);
>> bsTableEnv.registerDataStream("sample2", stream2);
>>
>> Table result = bsTableEnv.sqlQuery("SELECT * FROM sample1 FULL OUTER
>> JOIN sample2 on sample1.f0=sample2.f0");
>> result.printSchema();
>>
>> bsTableEnv.toAppendStream(result, Row.class).print();
>> bsTableEnv.execute("sample job");
>> }
>> }
>>
>>
>> 2) If I am using a blink planner should I use TableEnvironment or
>> StreamTableEnvironment ?
>>
>> 3) Why flink current stable documentation(1.9) recommends (old planner)?
>> any rough timeline on when we would be able to use blink planner in
>> production? perhaps 1.10 or 1.11?
>>
>> Thanks!
>>
>>
>>
