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https://issues.apache.org/jira/browse/FLINK-2828?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15258199#comment-15258199
]
ASF GitHub Bot commented on FLINK-2828:
---------------------------------------
Github user vasia commented on a diff in the pull request:
https://github.com/apache/flink/pull/1939#discussion_r61098440
--- Diff: docs/apis/batch/libs/table.md ---
@@ -67,6 +67,165 @@ The central concept of the Table API is a `Table` which
represents a table with
The following sections show by example how to use the Table API embedded
in the Scala and Java DataSet APIs.
+### Registering Tables to and Accessing Tables from TableEnvironments
+
+`TableEnvironment`s have an internal table catalog to which tables can be
registered with a unique name. After registration, a table can be accessed from
the `TableEnvironment` by its name. Tables can be registered in different ways.
+
+#### Register a DataSet
+
+A `DataSet` is registered as a `Table` in a `BatchTableEnvironment` as
follows:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
+BatchTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);
+
+// register the DataSet cust as table "Customers" with fields derived from
the dataset
+tableEnv.registerDataSet("Customers", cust)
+
+// register the DataSet ord as table "Orders" with fields user, product,
and amount
+tableEnv.registerDataSet("Orders", ord, "user, product, amount");
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val env = ExecutionEnvironment.getExecutionEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+// register the DataSet cust as table "Customers" with fields derived from
the dataset
+tableEnv.registerDataSet("Customers", cust)
+
+// register the DataSet ord as table "Orders" with fields user, product,
and amount
+tableEnv.registerDataSet("Orders", ord, 'user, 'product, 'amount)
+{% endhighlight %}
+</div>
+</div>
+
+*Note: DataSet table names are not allowed to follow the
`^_DataSetTable_[0-9]+` pattern, as these are reserved for internal use only.*
+
+#### Register a DataStream
+
+A `DataStream` is registered as a `Table` in a `StreamTableEnvironment` as
follows:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+StreamExecutionEnvironment env =
StreamExecutionEnvironment.getExecutionEnvironment();
+StreamTableEnvironment tableEnv =
TableEnvironment.getTableEnvironment(env);
+
+// register the DataStream cust as table "Customers" with fields derived
from the datastream
+tableEnv.registerDataStream("Customers", cust)
+
+// register the DataStream ord as table "Orders" with fields user,
product, and amount
+tableEnv.registerDataStream("Orders", ord, "user, product, amount");
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val env = StreamExecutionEnvironment.getExecutionEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+// register the DataStream cust as table "Customers" with fields derived
from the datastream
+tableEnv.registerDataStream("Customers", cust)
+
+// register the DataStream ord as table "Orders" with fields user,
product, and amount
+tableEnv.registerDataStream("Orders", ord, 'user, 'product, 'amount)
+{% endhighlight %}
+</div>
+</div>
+
+*Note: DataStream table names are not allowed to follow the
`^_DataStreamTable_[0-9]+` pattern, as these are reserved for internal use
only.*
+
+#### Register a Table
+
+A `Table` that originates from a Table API operation or a SQL query is
registered in a `TableEnvironemnt` as follows:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+// works for StreamExecutionEnvironment identically
+ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
+BatchTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);
+
+// convert a DataSet into a Table
+Table custT = tableEnv
+ .toTable(custDs, "name, zipcode")
+ .where("zipcode = '12345'")
+ .select("name")
+
+// register the Table custT as table "custNames"
+tableEnv.registerTable("custNames", custT)
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+// works for StreamExecutionEnvironment identically
+val env = ExecutionEnvironment.getExecutionEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+// convert a DataSet into a Table
+val custT = custDs
+ .toTable(tableEnv, 'name, 'zipcode)
+ .where('zipcode === "12345")
+ .select('name)
+
+// register the Table custT as table "custNames"
+tableEnv.registerTable("custNames", custT)
+{% endhighlight %}
+</div>
+</div>
+
+A registered `Table` that originates from a Table API operation or SQL
query is treated similarly as a view as known from relational DBMS, i.e., it
can be inlined when optimizing the query.
+
+#### Register an external table using a TableSource
--- End diff --
Capitalize Table to be consistent with previous titles?
> Add interfaces for Table API input formats
> ------------------------------------------
>
> Key: FLINK-2828
> URL: https://issues.apache.org/jira/browse/FLINK-2828
> Project: Flink
> Issue Type: New Feature
> Components: Table API
> Reporter: Timo Walther
> Assignee: Fabian Hueske
>
> In order to support input formats for the Table API, interfaces are
> necessary. I propose two types of TableSources:
> - AdaptiveTableSources can adapt their output to the requirements of the
> plan. Although the output schema stays the same, the TableSource can react on
> field resolution and/or predicates internally and can return adapted
> DataSet/DataStream versions in the "translate" step.
> - StaticTableSources are an easy way to provide the Table API with additional
> input formats without much implementation effort (e.g. for fromCsvFile())
> TableSources need to be deeply integrated into the Table API.
> The TableEnvironment requires a newly introduced AbstractExecutionEnvironment
> (common super class of all ExecutionEnvironments for DataSets and
> DataStreams).
> Here's what a TableSource can see from more complicated queries:
> {code}
> getTableJava(tableSource1)
> .filter("a===5 || a===6")
> .select("a as a4, b as b4, c as c4")
> .filter("b4===7")
> .join(getTableJava(tableSource2))
> .where("a===a4 && c==='Test' && c4==='Test2'")
> // Result predicates for tableSource1:
> // List("a===5 || a===6", "b===7", "c==='Test2'")
> // Result predicates for tableSource2:
> // List("c==='Test'")
> // Result resolved fields for tableSource1 (true = filtering,
> false=selection):
> // Set(("a", true), ("a", false), ("b", true), ("b", false), ("c", false),
> ("c", true))
> // Result resolved fields for tableSource2 (true = filtering,
> false=selection):
> // Set(("a", true), ("c", true))
> {code}
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