Hi Godfrey,

I was just clicking the run button on my IDE and it doesn't really show me
errors so I used command line fink run <jar> and that shows me what the
error is. It tells me I need to change to toRetractStream() and both
StreamExecutionEnvrionment and StreamTableEnvrionment .execute seems to
work fine although I am not sure which one is the correct usage.

Thanks!

On Sat, Jan 18, 2020 at 6:52 PM kant kodali <kanth...@gmail.com> wrote:

> 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!
>>>
>>>
>>>

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