CrynetLogistics commented on a change in pull request #18165:
URL: https://github.com/apache/flink/pull/18165#discussion_r783330823



##########
File path: docs/content/docs/connectors/datastream/kinesis.md
##########
@@ -566,124 +583,124 @@ Retry and backoff parameters can be configured using 
the `ConsumerConfigConstant
 this is called once per stream during stream consumer deregistration, unless 
the `NONE` or `EAGER` registration strategy is configured.
 Retry and backoff parameters can be configured using the 
`ConsumerConfigConstants.DEREGISTER_STREAM_*` keys.  
 
-## Kinesis Producer
-
-The `FlinkKinesisProducer` uses [Kinesis Producer Library 
(KPL)](http://docs.aws.amazon.com/streams/latest/dev/developing-producers-with-kpl.html)
 to put data from a Flink stream into a Kinesis stream.
-
-Note that the producer is not participating in Flink's checkpointing and 
doesn't provide exactly-once processing guarantees. Also, the Kinesis producer 
does not guarantee that records are written in order to the shards (See 
[here](https://github.com/awslabs/amazon-kinesis-producer/issues/23) and 
[here](http://docs.aws.amazon.com/kinesis/latest/APIReference/API_PutRecord.html#API_PutRecord_RequestSyntax)
 for more details).
+## Kinesis Data Streams Sink
 
-In case of a failure or a resharding, data will be written again to Kinesis, 
leading to duplicates. This behavior is usually called "at-least-once" 
semantics.
+The Kinesis Data Streams sink (hereafter "Kinesis sink") uses the [AWS v2 SDK 
for 
Java](https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/home.html)
 to write data from a Flink stream into a Kinesis stream.
 
-To put data into a Kinesis stream, make sure the stream is marked as "ACTIVE" 
in the AWS dashboard.
+To write data into a Kinesis stream, make sure the stream is marked as 
"ACTIVE" in the AWS dashboard.
 
 For the monitoring to work, the user accessing the stream needs access to the 
CloudWatch service.
 
 {{< tabs "6df3b696-c2ca-4f44-bea0-96cf8275d61c" >}}
 {{< tab "Java" >}}
 ```java
-Properties producerConfig = new Properties();
-// Required configs
-producerConfig.put(AWSConfigConstants.AWS_REGION, "us-east-1");
-producerConfig.put(AWSConfigConstants.AWS_ACCESS_KEY_ID, "aws_access_key_id");
-producerConfig.put(AWSConfigConstants.AWS_SECRET_ACCESS_KEY, 
"aws_secret_access_key");
-// Optional configs
-producerConfig.put("AggregationMaxCount", "4294967295");
-producerConfig.put("CollectionMaxCount", "1000");
-producerConfig.put("RecordTtl", "30000");
-producerConfig.put("RequestTimeout", "6000");
-producerConfig.put("ThreadPoolSize", "15");
-
-// Disable Aggregation if it's not supported by a consumer
-// producerConfig.put("AggregationEnabled", "false");
-// Switch KinesisProducer's threading model
-// producerConfig.put("ThreadingModel", "PER_REQUEST");
-
-FlinkKinesisProducer<String> kinesis = new FlinkKinesisProducer<>(new 
SimpleStringSchema(), producerConfig);
-kinesis.setFailOnError(true);
-kinesis.setDefaultStream("kinesis_stream_name");
-kinesis.setDefaultPartition("0");
+ElementConverter<String, PutRecordsRequestEntry> elementConverter =
+    KinesisDataStreamsSinkElementConverter.<String>builder()
+        .setSerializationSchema(new SimpleStringSchema())
+        .setPartitionKeyGenerator(element -> 
String.valueOf(element.hashCode()))
+        .build();
+
+Properties sinkProperties = new Properties();
+// Required
+sinkProperties.put(AWSConfigConstants.AWS_REGION, "us-east-1");
+sinkProperties.put(AWSConfigConstants.AWS_ACCESS_KEY_ID, "aws_access_key_id");
+sinkProperties.put(AWSConfigConstants.AWS_SECRET_ACCESS_KEY, 
"aws_secret_access_key");
+
+KinesisDataStreamsSink<String> kdsSink =
+    KinesisDataStreamsSink.<String>builder()
+        .setKinesisClientProperties(sinkProperties)    // Required
+        .setElementConverter(elementConverter)         // Required
+        .setStreamName("your-stream-name")             // Required
+        .setFailOnError(false)                         // Optional
+        .setMaxBatchSize(500)                          // Optional
+        .setMaxInFlightRequests(16)                    // Optional
+        .setMaxBufferedRequests(10_000)                // Optional
+        .setMaxBatchSizeInBytes(5 * 1024 * 1024)       // Optional
+        .setMaxTimeInBufferMS(5000)                    // Optional
+        .setMaxRecordSizeInBytes(1 * 1024 * 1024)      // Optional
+        .build();
 
 DataStream<String> simpleStringStream = ...;
-simpleStringStream.addSink(kinesis);
+simpleStringStream.sinkTo(kdsSink);
 ```
 {{< /tab >}}
 {{< tab "Scala" >}}
 ```scala
-val producerConfig = new Properties()
-// Required configs
-producerConfig.put(AWSConfigConstants.AWS_REGION, "us-east-1")
-producerConfig.put(AWSConfigConstants.AWS_ACCESS_KEY_ID, "aws_access_key_id")
-producerConfig.put(AWSConfigConstants.AWS_SECRET_ACCESS_KEY, 
"aws_secret_access_key")
-// Optional KPL configs
-producerConfig.put("AggregationMaxCount", "4294967295")
-producerConfig.put("CollectionMaxCount", "1000")
-producerConfig.put("RecordTtl", "30000")
-producerConfig.put("RequestTimeout", "6000")
-producerConfig.put("ThreadPoolSize", "15")
-
-// Disable Aggregation if it's not supported by a consumer
-// producerConfig.put("AggregationEnabled", "false")
-// Switch KinesisProducer's threading model
-// producerConfig.put("ThreadingModel", "PER_REQUEST")
-
-val kinesis = new FlinkKinesisProducer[String](new SimpleStringSchema, 
producerConfig)
-kinesis.setFailOnError(true)
-kinesis.setDefaultStream("kinesis_stream_name")
-kinesis.setDefaultPartition("0")
+val elementConverter =
+    KinesisDataStreamsSinkElementConverter.<String>builder()
+        .setSerializationSchema(new SimpleStringSchema())
+        .setPartitionKeyGenerator(element -> 
String.valueOf(element.hashCode()))
+        .build()
+
+val sinkProperties = new Properties()
+// Required
+sinkProperties.put(AWSConfigConstants.AWS_REGION, "us-east-1")
+sinkProperties.put(AWSConfigConstants.AWS_ACCESS_KEY_ID, "aws_access_key_id")
+sinkProperties.put(AWSConfigConstants.AWS_SECRET_ACCESS_KEY, 
"aws_secret_access_key")
+
+val kdsSink = KinesisDataStreamsSink.<String>builder()
+    .setKinesisClientProperties(sinkProperties)  // Required
+    .setElementConverter(elementConverter)       // Required
+    .setStreamName("your-stream-name")           // Required
+    .setFailOnError(false)                       // Optional
+    .setMaxBatchSize(500)                        // Optional
+    .setMaxInFlightRequests(16)                  // Optional
+    .setMaxBufferedRequests(10000)               // Optional
+    .setMaxBatchSizeInBytes(5 * 1024 * 1024)     // Optional
+    .setMaxTimeInBufferMS(5000)                  // Optional
+    .setMaxRecordSizeInBytes(1 * 1024 * 1024)    // Optional
+    .build()
 
 val simpleStringStream = ...
-simpleStringStream.addSink(kinesis)
+simpleStringStream.sinkTo(kdsSink)
 ```
 {{< /tab >}}
 {{< /tabs >}}
 
-The above is a simple example of using the producer. To initialize 
`FlinkKinesisProducer`, users are required to pass in `AWS_REGION`, 
`AWS_ACCESS_KEY_ID`, and `AWS_SECRET_ACCESS_KEY` via a `java.util.Properties` 
instance. Users can also pass in KPL's configurations as optional parameters to 
customize the KPL underlying `FlinkKinesisProducer`. The full list of KPL 
configs and explanations can be found 
[here](https://github.com/awslabs/amazon-kinesis-producer/blob/master/java/amazon-kinesis-producer-sample/default_config.properties).
 The example demonstrates producing a single Kinesis stream in the AWS region 
"us-east-1".
+The above is a simple example of using the Kinesis sink. Begin by creating a 
`java.util.Properties` instance with the `AWS_REGION`, `AWS_ACCESS_KEY_ID`, and 
`AWS_SECRET_ACCESS_KEY` configured. You can then construct the sink with the 
builder. The default values for the optional configurations are shown above.
 
-If users don't specify any KPL configs and values, `FlinkKinesisProducer` will 
use default config values of KPL, except `RateLimit`. `RateLimit` limits the 
maximum allowed put rate for a shard, as a percentage of the backend limits. 
KPL's default value is 150 but it makes KPL throw `RateLimitExceededException` 
too frequently and breaks Flink sink as a result. Thus `FlinkKinesisProducer` 
overrides KPL's default value to 100.
+You will always need to supply a `KinesisDataStreamsSinkElementConverter` 
during sink creation. This is where you specify your serialization schema and 
logic for generating a [partition 
key](https://docs.aws.amazon.com/streams/latest/dev/key-concepts.html#partition-key)
 from a record.
 
-Instead of a `SerializationSchema`, it also supports a 
`KinesisSerializationSchema`. The `KinesisSerializationSchema` allows to send 
the data to multiple streams. This is
-done using the `KinesisSerializationSchema.getTargetStream(T element)` method. 
Returning `null` there will instruct the producer to write the element to the 
default stream.
-Otherwise, the returned stream name is used.
+Some or all of the records in a request may fail to be persisted by Kinesis 
Data Streams for a number of reasons. If `failOnError` is on, then a runtime 
exception will be raised. Otherwise those records will be requeued in the 
buffer for retry.
 
-### Threading Model
+The Kinesis Sink provides some metrics through Flink's [metrics system]({{< 
ref "docs/ops/metrics" >}}) to analyze the behavior of the connector. A list of 
all exposed metrics may be found [here]({{<ref 
"docs/ops/metrics#kinesis-sink">}}).
 
-Since Flink 1.4.0, `FlinkKinesisProducer` switches its default underlying KPL 
from a one-thread-per-request mode to a thread-pool mode. KPL in thread-pool 
mode uses a queue and thread pool to execute requests to Kinesis. This limits 
the number of threads that KPL's native process may create, and therefore 
greatly lowers CPU utilization and improves efficiency. **Thus, We highly 
recommend Flink users use thread-pool model.** The default thread pool size is 
`10`. Users can set the pool size in `java.util.Properties` instance with key 
`ThreadPoolSize`, as shown in the above example.
+The sink default maximum record size is 1MB and maximum batch size is 5MB in 
line with the Kinesis Data Streams maximums.

Review comment:
       For sure.




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