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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-8240) Create unified interfaces to configure and instatiate TableSources
Date Fri, 26 Jan 2018 17:55:04 GMT

    [ https://issues.apache.org/jira/browse/FLINK-8240?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16341355#comment-16341355
] 

ASF GitHub Bot commented on FLINK-8240:
---------------------------------------

Github user fhueske commented on a diff in the pull request:

    https://github.com/apache/flink/pull/5240#discussion_r164168496
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/descriptors/Rowtime.scala
---
    @@ -0,0 +1,131 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one
    + * or more contributor license agreements.  See the NOTICE file
    + * distributed with this work for additional information
    + * regarding copyright ownership.  The ASF licenses this file
    + * to you under the Apache License, Version 2.0 (the
    + * "License"); you may not use this file except in compliance
    + * with the License.  You may obtain a copy of the License at
    + *
    + *     http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.flink.table.descriptors
    +
    +import org.apache.flink.table.api.Types
    +import org.apache.flink.table.descriptors.NormalizedProperties.{normalizeTimestampExtractor,
normalizeWatermarkStrategy}
    +import org.apache.flink.table.sources.tsextractors.{ExistingField, StreamRecordTimestamp,
TimestampExtractor}
    +import org.apache.flink.table.sources.wmstrategies.{AscendingTimestamps, BoundedOutOfOrderTimestamps,
PreserveWatermarks, WatermarkStrategy}
    +
    +import scala.collection.mutable
    +
    +/**
    +  * Rowtime descriptor for describing an event time attribute in the schema.
    +  */
    +class Rowtime extends Descriptor {
    +
    +  private var timestampExtractor: Option[TimestampExtractor] = None
    +  private var watermarkStrategy: Option[WatermarkStrategy] = None
    +
    +  /**
    +    * Sets a built-in timestamp extractor that converts an existing [[Long]] or
    +    * [[Types.SQL_TIMESTAMP]] field into the rowtime attribute.
    +    *
    +    * @param fieldName The field to convert into a rowtime attribute.
    +    */
    +  def timestampFromField(fieldName: String): Rowtime = {
    +    timestampExtractor = Some(new ExistingField(fieldName))
    +    this
    +  }
    +
    +  /**
    +    * Sets a built-in timestamp extractor that converts the assigned timestamp from
    +    * a DataStream API record into the rowtime attribute.
    +    *
    +    * Note: This extractor only works in streaming environments.
    +    */
    +  def timestampFromDataStream(): Rowtime = {
    +    timestampExtractor = Some(new StreamRecordTimestamp)
    +    this
    +  }
    +
    +  /**
    +    * Sets a custom timestamp extractor to be used for the rowtime attribute.
    +    *
    +    * @param extractor The [[TimestampExtractor]] to extract the rowtime attribute
    +    *                  from the physical type.
    +    */
    +  def timestampFromExtractor(extractor: TimestampExtractor): Rowtime = {
    +    timestampExtractor = Some(extractor)
    +    this
    +  }
    +
    +  /**
    +    * Sets a built-in watermark strategy for ascending rowtime attributes.
    +    *
    +    * Emits a watermark of the maximum observed timestamp so far minus 1.
    +    * Rows that have a timestamp equal to the max timestamp are not late.
    +    */
    +  def watermarkPeriodicAscending(): Rowtime = {
    +    watermarkStrategy = Some(new AscendingTimestamps)
    +    this
    +  }
    +
    +  /**
    +    * Sets a built-in watermark strategy for rowtime attributes which are out-of-order
by a bounded
    +    * time interval.
    +    *
    +    * Emits watermarks which are the maximum observed timestamp minus the specified delay.
    +    */
    +  def watermarkPeriodicBounding(delay: Long): Rowtime = {
    +    watermarkStrategy = Some(new BoundedOutOfOrderTimestamps(delay))
    +    this
    +  }
    +
    +  /**
    +    * Sets a built-in watermark strategy which indicates the watermarks should be preserved
from the
    +    * underlying DataStream API.
    +    */
    +  def watermarkFromDataStream(): Rowtime = {
    +    watermarkStrategy = Some(PreserveWatermarks.INSTANCE)
    +    this
    +  }
    +
    +  /**
    +    * Sets a custom watermark strategy to be used for the rowtime attribute.
    +    */
    +  def watermarkFromStrategy(strategy: WatermarkStrategy): Rowtime = {
    --- End diff --
    
    `watermarksFromStrategy()`


> Create unified interfaces to configure and instatiate TableSources
> ------------------------------------------------------------------
>
>                 Key: FLINK-8240
>                 URL: https://issues.apache.org/jira/browse/FLINK-8240
>             Project: Flink
>          Issue Type: New Feature
>          Components: Table API &amp; SQL
>            Reporter: Timo Walther
>            Assignee: Timo Walther
>            Priority: Major
>
> At the moment every table source has different ways for configuration and instantiation.
Some table source are tailored to a specific encoding (e.g., {{KafkaAvroTableSource}}, {{KafkaJsonTableSource}})
or only support one encoding for reading (e.g., {{CsvTableSource}}). Each of them might implement
a builder or support table source converters for external catalogs.
> The table sources should have a unified interface for discovery, defining common properties,
and instantiation. The {{TableSourceConverters}} provide a similar functionality but use an
external catalog. We might generialize this interface.
> In general a table source declaration depends on the following parts:
> {code}
> - Source
>   - Type (e.g. Kafka, Custom)
>   - Properties (e.g. topic, connection info)
> - Encoding
>   - Type (e.g. Avro, JSON, CSV)
>   - Schema (e.g. Avro class, JSON field names/types)
> - Rowtime descriptor/Proctime
>   - Watermark strategy and Watermark properties
>   - Time attribute info
> - Bucketization
> {code}
> This issue needs a design document before implementation. Any discussion is very welcome.



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