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Posted to commits@flink.apache.org by fh...@apache.org on 2017/06/15 09:44:05 UTC
[04/10] flink git commit: [FLNK-5354] [docs] Restructured Table API /
SQL docs
[FLNK-5354] [docs] Restructured Table API / SQL docs
Project: http://git-wip-us.apache.org/repos/asf/flink/repo
Commit: http://git-wip-us.apache.org/repos/asf/flink/commit/a5d93a56
Tree: http://git-wip-us.apache.org/repos/asf/flink/tree/a5d93a56
Diff: http://git-wip-us.apache.org/repos/asf/flink/diff/a5d93a56
Branch: refs/heads/master
Commit: a5d93a56cb37e691ec9bb06d17c76151e7619267
Parents: 9141379
Author: Fabian Hueske <fh...@apache.org>
Authored: Tue May 23 16:19:49 2017 +0100
Committer: Fabian Hueske <fh...@apache.org>
Committed: Thu Jun 15 11:41:59 2017 +0200
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docs/dev/table/common.md | 548 ++++
docs/dev/table/sourceSinks.md | 286 ++
docs/dev/table/sql.md | 1778 +++++++++++
docs/dev/table/streaming.md | 67 +
docs/dev/table/tableApi.md | 3559 +++++++++++++++++++++
docs/dev/table/udfs.md | 362 +++
docs/dev/tableApi.md | 81 +
docs/dev/table_api.md | 6015 ------------------------------------
8 files changed, 6681 insertions(+), 6015 deletions(-)
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http://git-wip-us.apache.org/repos/asf/flink/blob/a5d93a56/docs/dev/table/common.md
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diff --git a/docs/dev/table/common.md b/docs/dev/table/common.md
new file mode 100644
index 0000000..d0d4914
--- /dev/null
+++ b/docs/dev/table/common.md
@@ -0,0 +1,548 @@
+---
+title: "Concepts & Common API"
+nav-parent_id: tableapi
+nav-pos: 0
+---
+<!--
+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.
+-->
+
+The Table API and SQL are integrated API and share many concepts and much of their API.
+
+**TODO: Extend**
+
+* This will be replaced by the TOC
+{:toc}
+
+Structure of Table API and SQL Programs
+---------------------------------------
+
+All Table API and SQL programs for batch and streaming have the same structure.
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
+
+// Create a TableEnvironment
+StreamTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);
+
+// Register a Table
+tableEnv.registerTable("yourTable", ...) // or
+tableEnv.registerTableSource("yourTableSrc", ...); // or
+tableEnv.registerDataStream("yourTableStream", ...); // or
+tableEnv.registerDataSet("yourTableSet", ...); // or
+tableEnv.registerExternalCatalog("yourCatalog", ...);
+
+// Create a table from a Table API query
+Table tapiResult = tableEnv.scan("yourTableSrc").select(...);
+// Or create a table from a SQL query
+Table sqlResult = tableEnv.sql("SELECT ... FROM yourTableSrc ... ");
+
+// Emit a Table to a TableSink / DataStream / DataSet
+resultTable.writeToSink(...); // or
+resultTable.toAppendStream(...); // or
+resultTable.toRetractStream(...); // or
+resultTable.toDataSet(...);
+
+// Execute
+env.execute("Your Query");
+
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val env = ExecutionEnvironment.getExecutionEnvironment
+
+// Create a TableEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+// Register a Table
+tableEnv.registerTable("yourTable", ...) // or
+tableEnv.registerTableSource("yourTableSrc", ...) // or
+tableEnv.registerDataStream("yourTableStream", ...) // or
+tableEnv.registerDataSet("yourTableSet", ...) // or
+tableEnv.registerExternalCatalog("yourCatalog", ...)
+
+// Create a table from a Table API query
+val tapiResult = tableEnv.scan("yourTableSrc").select(...)
+// Or create a table from a SQL query
+val sqlResult = tableEnv.sql("SELECT ... FROM yourTableSrc ...")
+
+// Emit a Table
+resultTable.writeToSink(...) // or
+resultTable.toAppendStream(...) // or
+resultTable.toRetractStream(...) // or
+resultTable.toDataSet(...)
+
+// Execute
+env.execute("Your Query")
+
+{% endhighlight %}
+</div>
+</div>
+
+{% top %}
+
+Create a TableEnvironment
+-------------------------
+
+A `Table` is always bound to a specific `TableEnvironment`. It is not possible to combine Tables of different TableEnvironments.
+
+**TODO: Extend**
+
+{% top %}
+
+Register a Table in the Catalog
+-------------------------------
+
+`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.
+
+*Note: `DataSet`s or `DataStream`s can be directly converted into `Table`s without registering them in the `TableEnvironment`. See [Create a Table from a DataStream or DataSet](#tbd) for details.
+
+### Register a Table
+
+A `Table` that originates from a Table API operation or a SQL query is registered in a `TableEnvironment` 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.
+
+{% top %}
+
+### 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: The name of a `DataSet` `Table` must not match the `^_DataSetTable_[0-9]+` pattern which is reserved for internal use only.*
+
+{% top %}
+
+### 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: The name of a `DataStream` `Table` must not match the `^_DataStreamTable_[0-9]+` pattern which is reserved for internal use only.*
+
+{% top %}
+
+### Register a TableSource
+
+TableSources provided access to data stored in various storage systems such as databases (MySQL, HBase, ...), file formats (CSV, Apache Parquet, Avro, ORC, ...), or messaging systems (Apache Kafka, RabbitMQ, ...). Flink provides a TableSources for common data formats and storage systems. Please have a look at the [Table Sources and Sinks page]({{ site.baseurl }}/dev/table/sourceSinks.html) for a list of provided TableSources and documentation for how to built your own.
+
+An external table is registered in a `TableEnvironment` using a `TableSource` 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);
+
+TableSource custTS = new CsvTableSource("/path/to/file", ...);
+
+// register a `TableSource` as external table "Customers"
+tableEnv.registerTableSource("Customers", custTS);
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+// works for StreamExecutionEnvironment identically
+val env = ExecutionEnvironment.getExecutionEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+val custTS: TableSource = new CsvTableSource("/path/to/file", ...)
+
+// register a `TableSource` as external table "Customers"
+tableEnv.registerTableSource("Customers", custTS)
+
+{% endhighlight %}
+</div>
+</div>
+
+A `TableSource` can provide access to data stored in various storage systems such as databases (MySQL, HBase, ...), file formats (CSV, Apache Parquet, Avro, ORC, ...), or messaging systems (Apache Kafka, RabbitMQ, ...).
+
+{% top %}
+
+Register an External Catalog
+----------------------------
+
+An external catalog is defined by the `ExternalCatalog` interface and provides information about databases and tables such as their name, schema, statistics, and access information. An `ExternalCatalog` is registered in a `TableEnvironment` 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);
+
+ExternalCatalog customerCatalog = new InMemoryExternalCatalog();
+
+// register the ExternalCatalog customerCatalog
+tableEnv.registerExternalCatalog("Customers", customerCatalog);
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+// works for StreamExecutionEnvironment identically
+val env = ExecutionEnvironment.getExecutionEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+val customerCatalog: ExternalCatalog = new InMemoryExternalCatalog
+
+// register the ExternalCatalog customerCatalog
+tableEnv.registerExternalCatalog("Customers", customerCatalog)
+
+{% endhighlight %}
+</div>
+</div>
+
+Once registered in a `TableEnvironment`, all tables defined in a `ExternalCatalog` can be accessed from Table API or SQL queries by specifying their full path (`catalog`.`database`.`table`).
+
+Currently, Flink provides an `InMemoryExternalCatalog` for demo and testing purposes. However, the `ExternalCatalog` interface can also be used to connect catalogs like HCatalog or Metastore to the Table API.
+
+{% top %}
+
+Create a Table from a DataStream or DataSet
+-------------------------------------------
+
+Besides registering a Table in a catalog, it is also possible to directly create a `Table` from a `DataStream` or `DataSet`.
+
+### Create a Table from a DataStream
+
+**TODO**
+
+{% top %}
+
+### Create a Table from a DataSet
+
+**TODO**
+
+### Scala Implicit Conversion
+
+If you use the Scala API, A `DataSet` or `DataStream` can be implicitly converted into a `Table`.
+
+{% top %}
+
+Query a Table
+-------------
+
+### Table API
+
+**TODO**
+
+{% top %}
+
+### SQL
+
+**TODO**
+
+{% top %}
+
+### Interoperability
+
+**TODO**
+
+* Mix SQL and Table as you like
+* Table API to SQL requires registered tables, register Table
+* SQL to Table API just use resulting table
+
+{% top %}
+
+Emit a Table
+------------
+
+### Emit to a TableSink
+
+A `Table` can be written to a `TableSink`, which is a generic interface to support a wide variety of file formats (e.g. CSV, Apache Parquet, Apache Avro), storage systems (e.g., JDBC, Apache HBase, Apache Cassandra, Elasticsearch), or messaging systems (e.g., Apache Kafka, RabbitMQ). A batch `Table` can only be written to a `BatchTableSink`, a streaming table requires a `StreamTableSink`. A `TableSink` can implement both interfaces at the same time.
+
+Currently, Flink only provides a `CsvTableSink` that writes a batch or streaming `Table` to CSV-formatted files. A custom `TableSink` can be defined by implementing the `BatchTableSink` and/or `StreamTableSink` interface.
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
+BatchTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);
+
+// compute the result Table using Table API operators and/or SQL queries
+Table result = ...
+
+// create a TableSink
+TableSink sink = new CsvTableSink("/path/to/file", fieldDelim = "|");
+// write the result Table to the TableSink
+result.writeToSink(sink);
+
+// execute the program
+env.execute();
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val env = ExecutionEnvironment.getExecutionEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+// compute the result Table using Table API operators and/or SQL queries
+val result: Table = ...
+
+// create a TableSink
+val sink: TableSink = new CsvTableSink("/path/to/file", fieldDelim = "|")
+// write the result Table to the TableSink
+result.writeToSink(sink)
+
+// execute the program
+env.execute()
+{% endhighlight %}
+</div>
+</div>
+
+{% top %}
+
+### Convert to a DataStream
+
+**TODO**
+
+{% top %}
+
+### Convert to a DataSet
+
+**TODO**
+
+### Scala Implicit Conversion
+
+If you use the Scala API, A `Table` can be implicitly converted into a `DataSet` or `DataStream`.
+
+{% top %}
+
+Execute a Query
+---------------
+
+**TODO**
+
+{% top %}
+
+Mappings Types to Table Schema
+------------------------------
+
+* Explain how types are mapped to table schema
+ * Atomic Types
+ * Row
+ * Tuples (Java / Scala)
+ * Pojos
+ * Case Classes
+
+**TODO**
+
+{% top %}
+
+Integration with DataSet and DataStream API
+-------------------------------------------
+
+**TODO**
+
+* Create `Table` from `DataSet` and `DataStream` and back
+* Easy integration with more expressive APIs and libraries
+ * CEP / Gelly / ML
+ * Ingestion and projection
+
+{% top %}
+
+Query Optimization
+------------------
+
+* No join order yet
+* Filter / Projection push down
+* Custom rules
+
+### Explaining a Table
+
+The Table API provides a mechanism to explain the logical and optimized query plans to compute a `Table`.
+This is done through the `TableEnvironment#explain(table)` method. It returns a string describing three plans:
+
+1. the Abstract Syntax Tree of the relational query, i.e., the unoptimized logical query plan,
+2. the optimized logical query plan, and
+3. the physical execution plan.
+
+The following code shows an example and the corresponding output:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
+StreamTableEnvironment tEnv = TableEnvironment.getTableEnvironment(env);
+
+DataStream<Tuple2<Integer, String>> stream1 = env.fromElements(new Tuple2<>(1, "hello"));
+DataStream<Tuple2<Integer, String>> stream2 = env.fromElements(new Tuple2<>(1, "hello"));
+
+Table table1 = tEnv.fromDataStream(stream1, "count, word");
+Table table2 = tEnv.fromDataStream(stream2, "count, word");
+Table table = table1
+ .where("LIKE(word, 'F%')")
+ .unionAll(table2);
+
+String explanation = tEnv.explain(table);
+System.out.println(explanation);
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val env = StreamExecutionEnvironment.getExecutionEnvironment
+val tEnv = TableEnvironment.getTableEnvironment(env)
+
+val table1 = env.fromElements((1, "hello")).toTable(tEnv, 'count, 'word)
+val table2 = env.fromElements((1, "hello")).toTable(tEnv, 'count, 'word)
+val table = table1
+ .where('word.like("F%"))
+ .unionAll(table2)
+
+val explanation: String = tEnv.explain(table)
+println(explanation)
+{% endhighlight %}
+</div>
+</div>
+
+{% highlight text %}
+== Abstract Syntax Tree ==
+LogicalUnion(all=[true])
+ LogicalFilter(condition=[LIKE($1, 'F%')])
+ LogicalTableScan(table=[[_DataStreamTable_0]])
+ LogicalTableScan(table=[[_DataStreamTable_1]])
+
+== Optimized Logical Plan ==
+DataStreamUnion(union=[count, word])
+ DataStreamCalc(select=[count, word], where=[LIKE(word, 'F%')])
+ DataStreamScan(table=[[_DataStreamTable_0]])
+ DataStreamScan(table=[[_DataStreamTable_1]])
+
+== Physical Execution Plan ==
+Stage 1 : Data Source
+ content : collect elements with CollectionInputFormat
+
+Stage 2 : Data Source
+ content : collect elements with CollectionInputFormat
+
+ Stage 3 : Operator
+ content : from: (count, word)
+ ship_strategy : REBALANCE
+
+ Stage 4 : Operator
+ content : where: (LIKE(word, 'F%')), select: (count, word)
+ ship_strategy : FORWARD
+
+ Stage 5 : Operator
+ content : from: (count, word)
+ ship_strategy : REBALANCE
+{% endhighlight %}
+
+{% top %}
+
+
http://git-wip-us.apache.org/repos/asf/flink/blob/a5d93a56/docs/dev/table/sourceSinks.md
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diff --git a/docs/dev/table/sourceSinks.md b/docs/dev/table/sourceSinks.md
new file mode 100644
index 0000000..2d07254
--- /dev/null
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@@ -0,0 +1,286 @@
+---
+title: "Table Sources & Sinks"
+nav-parent_id: tableapi
+nav-pos: 40
+---
+<!--
+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.
+-->
+
+* This will be replaced by the TOC
+{:toc}
+
+Provided TableSources
+---------------------
+
+**TODO: extend and complete**
+
+Currently, Flink provides the `CsvTableSource` to read CSV files and various `TableSources` to read JSON or Avro objects from Kafka.
+A custom `TableSource` can be defined by implementing the `BatchTableSource` or `StreamTableSource` interface.
+
+| **Class name** | **Maven dependency** | **Batch?** | **Streaming?** | **Description**
+| `CsvTableSouce` | `flink-table` | Y | Y | A simple source for CSV files.
+| `Kafka08JsonTableSource` | `flink-connector-kafka-0.8` | N | Y | A Kafka 0.8 source for JSON data.
+| `Kafka08AvroTableSource` | `flink-connector-kafka-0.8` | N | Y | A Kafka 0.8 source for Avro data.
+| `Kafka09JsonTableSource` | `flink-connector-kafka-0.9` | N | Y | A Kafka 0.9 source for JSON data.
+| `Kafka09AvroTableSource` | `flink-connector-kafka-0.9` | N | Y | A Kafka 0.9 source for Avro data.
+| `Kafka010JsonTableSource` | `flink-connector-kafka-0.10` | N | Y | A Kafka 0.10 source for JSON data.
+| `Kafka010AvroTableSource` | `flink-connector-kafka-0.10` | N | Y | A Kafka 0.10 source for Avro data.
+
+All sources that come with the `flink-table` dependency can be directly used by your Table programs. For all other table sources, you have to add the respective dependency in addition to the `flink-table` dependency.
+
+{% top %}
+
+### KafkaJsonTableSource
+
+To use the Kafka JSON source, you have to add the Kafka connector dependency to your project:
+
+ - `flink-connector-kafka-0.8` for Kafka 0.8,
+ - `flink-connector-kafka-0.9` for Kafka 0.9, or
+ - `flink-connector-kafka-0.10` for Kafka 0.10, respectively.
+
+You can then create the source as follows (example for Kafka 0.8):
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+// specify JSON field names and types
+TypeInformation<Row> typeInfo = Types.ROW(
+ new String[] { "id", "name", "score" },
+ new TypeInformation<?>[] { Types.INT(), Types.STRING(), Types.DOUBLE() }
+);
+
+KafkaJsonTableSource kafkaTableSource = new Kafka08JsonTableSource(
+ kafkaTopic,
+ kafkaProperties,
+ typeInfo);
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+// specify JSON field names and types
+val typeInfo = Types.ROW(
+ Array("id", "name", "score"),
+ Array(Types.INT, Types.STRING, Types.DOUBLE)
+)
+
+val kafkaTableSource = new Kafka08JsonTableSource(
+ kafkaTopic,
+ kafkaProperties,
+ typeInfo)
+{% endhighlight %}
+</div>
+</div>
+
+By default, a missing JSON field does not fail the source. You can configure this via:
+
+```java
+// Fail on missing JSON field
+tableSource.setFailOnMissingField(true);
+```
+
+You can work with the Table as explained in the rest of the Table API guide:
+
+```java
+tableEnvironment.registerTableSource("kafka-source", kafkaTableSource);
+Table result = tableEnvironment.scan("kafka-source");
+```
+
+{% top %}
+
+### KafkaAvroTableSource
+
+The `KafkaAvroTableSource` allows you to read Avro's `SpecificRecord` objects from Kafka.
+
+To use the Kafka Avro source, you have to add the Kafka connector dependency to your project:
+
+ - `flink-connector-kafka-0.8` for Kafka 0.8,
+ - `flink-connector-kafka-0.9` for Kafka 0.9, or
+ - `flink-connector-kafka-0.10` for Kafka 0.10, respectively.
+
+You can then create the source as follows (example for Kafka 0.8):
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+// pass the generated Avro class to the TableSource
+Class<? extends SpecificRecord> clazz = MyAvroType.class;
+
+KafkaAvroTableSource kafkaTableSource = new Kafka08AvroTableSource(
+ kafkaTopic,
+ kafkaProperties,
+ clazz);
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+// pass the generated Avro class to the TableSource
+val clazz = classOf[MyAvroType]
+
+val kafkaTableSource = new Kafka08AvroTableSource(
+ kafkaTopic,
+ kafkaProperties,
+ clazz)
+{% endhighlight %}
+</div>
+</div>
+
+{% top %}
+
+### CsvTableSource
+
+The `CsvTableSource` is already included in `flink-table` without additional dependecies.
+
+The easiest way to create a `CsvTableSource` is by using the enclosed builder `CsvTableSource.builder()`, the builder has the following methods to configure properties:
+
+ - `path(String path)` Sets the path to the CSV file, required.
+ - `field(String fieldName, TypeInformation<?> fieldType)` Adds a field with the field name and field type information, can be called multiple times, required. The call order of this method defines also the order of the fields in a row.
+ - `fieldDelimiter(String delim)` Sets the field delimiter, `","` by default.
+ - `lineDelimiter(String delim)` Sets the line delimiter, `"\n"` by default.
+ - `quoteCharacter(Character quote)` Sets the quote character for String values, `null` by default.
+ - `commentPrefix(String prefix)` Sets a prefix to indicate comments, `null` by default.
+ - `ignoreFirstLine()` Ignore the first line. Disabled by default.
+ - `ignoreParseErrors()` Skip records with parse error instead to fail. Throwing an exception by default.
+
+You can create the source as follows:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+CsvTableSource csvTableSource = CsvTableSource
+ .builder()
+ .path("/path/to/your/file.csv")
+ .field("name", Types.STRING())
+ .field("id", Types.INT())
+ .field("score", Types.DOUBLE())
+ .field("comments", Types.STRING())
+ .fieldDelimiter("#")
+ .lineDelimiter("$")
+ .ignoreFirstLine()
+ .ignoreParseErrors()
+ .commentPrefix("%");
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val csvTableSource = CsvTableSource
+ .builder
+ .path("/path/to/your/file.csv")
+ .field("name", Types.STRING)
+ .field("id", Types.INT)
+ .field("score", Types.DOUBLE)
+ .field("comments", Types.STRING)
+ .fieldDelimiter("#")
+ .lineDelimiter("$")
+ .ignoreFirstLine
+ .ignoreParseErrors
+ .commentPrefix("%")
+{% endhighlight %}
+</div>
+</div>
+
+You can work with the Table as explained in the rest of the Table API guide in both stream and batch `TableEnvironment`s:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+tableEnvironment.registerTableSource("mycsv", csvTableSource);
+
+Table streamTable = streamTableEnvironment.scan("mycsv");
+
+Table batchTable = batchTableEnvironment.scan("mycsv");
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+tableEnvironment.registerTableSource("mycsv", csvTableSource)
+
+val streamTable = streamTableEnvironment.scan("mycsv")
+
+val batchTable = batchTableEnvironment.scan("mycsv")
+{% endhighlight %}
+</div>
+</div>
+
+{% top %}
+
+Provided TableSinks
+-------------------
+
+**TODO**
+
+{% top %}
+
+Define a TableSource
+--------------------
+
+### BatchTableSource
+
+**TODO**
+
+{% top %}
+
+### StreamTableSource
+* TimestampAssigner
+* DefinedRowtimeAttribute / DefinedProctimeAttribute
+
+**TODO**
+
+{% top %}
+
+### ProjectableTableSource
+
+**TODO**
+
+{% top %}
+
+### FilterableTableSource
+
+**TODO**
+
+{% top %}
+
+Define a TableSink
+------------------
+
+### BatchTableSink
+
+**TODO**
+
+{% top %}
+
+### AppendStreamTableSink
+
+**TODO**
+
+{% top %}
+
+### RetractStreamTableSink
+
+**TODO**
+
+{% top %}
+
+### UpsertStreamTableSInk
+
+**TODO**
+
+{% top %}
+
http://git-wip-us.apache.org/repos/asf/flink/blob/a5d93a56/docs/dev/table/sql.md
----------------------------------------------------------------------
diff --git a/docs/dev/table/sql.md b/docs/dev/table/sql.md
new file mode 100644
index 0000000..b79f4f2
--- /dev/null
+++ b/docs/dev/table/sql.md
@@ -0,0 +1,1778 @@
+---
+title: "SQL"
+nav-parent_id: tableapi
+nav-pos: 30
+---
+<!--
+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.
+-->
+
+SQL queries are specified using the `sql()` method of the `TableEnvironment`. The method returns the result of the SQL query as a `Table` which can be converted into a `DataSet` or `DataStream`, used in subsequent Table API queries, or written to a `TableSink` (see [Writing Tables to External Sinks](#writing-tables-to-external-sinks)). SQL and Table API queries can seamlessly mixed and are holistically optimized and translated into a single DataStream or DataSet program.
+
+A `Table`, `DataSet`, `DataStream`, or external `TableSource` must be registered in the `TableEnvironment` in order to be accessible by a SQL query (see [Registering Tables](#registering-tables)). For convenience `Table.toString()` will automatically register an unique table name under the `Table`'s `TableEnvironment` and return the table name. So it allows to call SQL directly on tables in a string concatenation (see examples below).
+
+*Note: Flink's SQL support is not feature complete, yet. Queries that include unsupported SQL features will cause a `TableException`. The limitations of SQL on batch and streaming tables are listed in the following sections.*
+
+**TODO: Rework intro. Move some parts below. **
+
+* This will be replaced by the TOC
+{:toc}
+
+Specifying a Query
+---------------
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
+StreamTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);
+
+// ingest a DataStream from an external source
+DataStream<Tuple3<Long, String, Integer>> ds = env.addSource(...);
+
+// call SQL on unregistered tables
+Table table = tableEnv.toTable(ds, "user, product, amount");
+Table result = tableEnv.sql(
+ "SELECT SUM(amount) FROM " + table + " WHERE product LIKE '%Rubber%'");
+
+// call SQL on registered tables
+// register the DataStream as table "Orders"
+tableEnv.registerDataStream("Orders", ds, "user, product, amount");
+// run a SQL query on the Table and retrieve the result as a new Table
+Table result2 = tableEnv.sql(
+ "SELECT product, amount FROM Orders WHERE product LIKE '%Rubber%'");
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val env = StreamExecutionEnvironment.getExecutionEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+// read a DataStream from an external source
+val ds: DataStream[(Long, String, Integer)] = env.addSource(...)
+
+// call SQL on unregistered tables
+val table = ds.toTable(tableEnv, 'user, 'product, 'amount)
+val result = tableEnv.sql(
+ s"SELECT SUM(amount) FROM $table WHERE product LIKE '%Rubber%'")
+
+// call SQL on registered tables
+// register the DataStream under the name "Orders"
+tableEnv.registerDataStream("Orders", ds, 'user, 'product, 'amount)
+// run a SQL query on the Table and retrieve the result as a new Table
+val result2 = tableEnv.sql(
+ "SELECT product, amount FROM Orders WHERE product LIKE '%Rubber%'")
+{% endhighlight %}
+</div>
+</div>
+
+**TODO: Add some intro.**
+
+{% top %}
+
+Supported Syntax
+----------------
+
+Flink uses [Apache Calcite](https://calcite.apache.org/docs/reference.html) for SQL parsing. Currently, Flink SQL only supports query-related SQL syntax and only a subset of the comprehensive SQL standard. The following BNF-grammar describes the supported SQL features:
+
+```
+
+query:
+ values
+ | {
+ select
+ | selectWithoutFrom
+ | query UNION [ ALL ] query
+ | query EXCEPT query
+ | query INTERSECT query
+ }
+ [ ORDER BY orderItem [, orderItem ]* ]
+ [ LIMIT { count | ALL } ]
+ [ OFFSET start { ROW | ROWS } ]
+ [ FETCH { FIRST | NEXT } [ count ] { ROW | ROWS } ONLY]
+
+orderItem:
+ expression [ ASC | DESC ]
+
+select:
+ SELECT [ ALL | DISTINCT ]
+ { * | projectItem [, projectItem ]* }
+ FROM tableExpression
+ [ WHERE booleanExpression ]
+ [ GROUP BY { groupItem [, groupItem ]* } ]
+ [ HAVING booleanExpression ]
+
+selectWithoutFrom:
+ SELECT [ ALL | DISTINCT ]
+ { * | projectItem [, projectItem ]* }
+
+projectItem:
+ expression [ [ AS ] columnAlias ]
+ | tableAlias . *
+
+tableExpression:
+ tableReference [, tableReference ]*
+ | tableExpression [ NATURAL ] [ LEFT | RIGHT | FULL ] JOIN tableExpression [ joinCondition ]
+
+joinCondition:
+ ON booleanExpression
+ | USING '(' column [, column ]* ')'
+
+tableReference:
+ tablePrimary
+ [ [ AS ] alias [ '(' columnAlias [, columnAlias ]* ')' ] ]
+
+tablePrimary:
+ [ TABLE ] [ [ catalogName . ] schemaName . ] tableName
+ | LATERAL TABLE '(' functionName '(' expression [, expression ]* ')' ')'
+ | UNNEST '(' expression ')'
+
+values:
+ VALUES expression [, expression ]*
+
+groupItem:
+ expression
+ | '(' ')'
+ | '(' expression [, expression ]* ')'
+ | CUBE '(' expression [, expression ]* ')'
+ | ROLLUP '(' expression [, expression ]* ')'
+ | GROUPING SETS '(' groupItem [, groupItem ]* ')'
+```
+
+For a better definition of SQL queries within a Java String, Flink SQL uses a lexical policy similar to Java:
+
+- The case of identifiers is preserved whether or not they are quoted.
+- After which, identifiers are matched case-sensitively.
+- Unlike Java, back-ticks allow identifiers to contain non-alphanumeric characters (e.g. <code>"SELECT a AS `my field` FROM t"</code>).
+
+{% top %}
+
+Example Queries
+---------------
+
+**TODO: Add a examples for different operations with similar structure as for the Table API. Add highlighted tags if an operation is not supported by stream / batch.**
+
+* Scan & Values
+* Selection & Projection
+* Aggregations (distinct only Batch)
+ * GroupBy
+ * GroupBy Windows (TUMBLE, HOP, SESSION)
+ * OVER windows (Only Stream)
+ * Grouping sets, rollup, cube (only batch)
+ * Having (only batch?)
+* Joins
+ * Inner equi joins (only batch)
+ * Outer equi joins (only batch)
+ * TableFunction
+* Set operations (only batch, except Union ALL)
+* OrderBy + Limit + Offset
+
+{% top %}
+
+### GroupBy Windows
+
+**TODO: Integrate this with the examples**
+
+### Group Windows
+
+Group windows are defined in the `GROUP BY` clause of a SQL query. Just like queries with regular `GROUP BY` clauses, queries with a `GROUP BY` clause that includes a group window function compute a single result row per group. The following group windows functions are supported for SQL on batch and streaming tables.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 30%">Group Window Function</th>
+ <th class="text-left">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td><code>TUMBLE(time_attr, interval)</code></td>
+ <td>Defines a tumbling time window. A tumbling time window assigns rows to non-overlapping, continuous windows with a fixed duration (<code>interval</code>). For example, a tumbling window of 5 minutes groups rows in 5 minutes intervals. Tumbling windows can be defined on event-time (stream + batch) or processing-time (stream).</td>
+ </tr>
+ <tr>
+ <td><code>HOP(time_attr, interval, interval)</code></td>
+ <td>Defines a hopping time window (called sliding window in the Table API). A hopping time window has a fixed duration (second <code>interval</code> parameter) and hops by a specified hop interval (first <code>interval</code> parameter). If the hop interval is smaller than the window size, hopping windows are overlapping. Thus, rows can be assigned to multiple windows. For example, a hopping window of 15 minutes size and 5 minute hop interval assigns each row to 3 different windows of 15 minute size, which are evaluated in an interval of 5 minutes. Hopping windows can be defined on event-time (stream + batch) or processing-time (stream).</td>
+ </tr>
+ <tr>
+ <td><code>SESSION(time_attr, interval)</code></td>
+ <td>Defines a session time window. Session time windows do not have a fixed duration but their bounds are defined by a time <code>interval</code> of inactivity, i.e., a session window is closed if no event appears for a defined gap period. For example a session window with a 30 minute gap starts when a row is observed after 30 minutes inactivity (otherwise the row would be added to an existing window) and is closed if no row is added within 30 minutes. Session windows can work on event-time (stream + batch) or processing-time (stream).</td>
+ </tr>
+ </tbody>
+</table>
+
+For SQL queries on streaming tables, the `time_attr` argument of the group window function must be one of the `rowtime()` or `proctime()` time-indicators, which distinguish between event or processing time, respectively. For SQL on batch tables, the `time_attr` argument of the group window function must be an attribute of type `TIMESTAMP`.
+
+#### Selecting Group Window Start and End Timestamps
+
+The start and end timestamps of group windows can be selected with the following auxiliary functions:
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Auxiliary Function</th>
+ <th class="text-left">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ <code>TUMBLE_START(time_attr, interval)</code><br/>
+ <code>HOP_START(time_attr, interval, interval)</code><br/>
+ <code>SESSION_START(time_attr, interval)</code><br/>
+ </td>
+ <td>Returns the start timestamp of the corresponding tumbling, hopping, and session window.</td>
+ </tr>
+ <tr>
+ <td>
+ <code>TUMBLE_END(time_attr, interval)</code><br/>
+ <code>HOP_END(time_attr, interval, interval)</code><br/>
+ <code>SESSION_END(time_attr, interval)</code><br/>
+ </td>
+ <td>Returns the end timestamp of the corresponding tumbling, hopping, and session window.</td>
+ </tr>
+ </tbody>
+</table>
+
+Note that the auxiliary functions must be called with exactly same arguments as the group window function in the `GROUP BY` clause.
+
+The following examples show how to specify SQL queries with group windows on streaming tables.
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
+StreamTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);
+
+// ingest a DataStream from an external source
+DataStream<Tuple3<Long, String, Integer>> ds = env.addSource(...);
+// register the DataStream as table "Orders"
+tableEnv.registerDataStream("Orders", ds, "user, product, amount");
+
+// compute SUM(amount) per day (in event-time)
+Table result1 = tableEnv.sql(
+ "SELECT user, " +
+ " TUMBLE_START(rowtime(), INTERVAL '1' DAY) as wStart, " +
+ " SUM(amount) FROM Orders " +
+ "GROUP BY TUMBLE(rowtime(), INTERVAL '1' DAY), user");
+
+// compute SUM(amount) per day (in processing-time)
+Table result2 = tableEnv.sql(
+ "SELECT user, SUM(amount) FROM Orders GROUP BY TUMBLE(proctime(), INTERVAL '1' DAY), user");
+
+// compute every hour the SUM(amount) of the last 24 hours in event-time
+Table result3 = tableEnv.sql(
+ "SELECT product, SUM(amount) FROM Orders GROUP BY HOP(rowtime(), INTERVAL '1' HOUR, INTERVAL '1' DAY), product");
+
+// compute SUM(amount) per session with 12 hour inactivity gap (in event-time)
+Table result4 = tableEnv.sql(
+ "SELECT user, " +
+ " SESSION_START(rowtime(), INTERVAL '12' HOUR) AS sStart, " +
+ " SESSION_END(rowtime(), INTERVAL '12' HOUR) AS snd, " +
+ " SUM(amount) " +
+ "FROM Orders " +
+ "GROUP BY SESSION(rowtime(), INTERVAL '12' HOUR), user");
+
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val env = StreamExecutionEnvironment.getExecutionEnvironment
+val tableEnv = TableEnvironment.getTableEnvironment(env)
+
+// read a DataStream from an external source
+val ds: DataStream[(Long, String, Int)] = env.addSource(...)
+// register the DataStream under the name "Orders"
+tableEnv.registerDataStream("Orders", ds, 'user, 'product, 'amount)
+
+// compute SUM(amount) per day (in event-time)
+val result1 = tableEnv.sql(
+ """
+ |SELECT
+ | user,
+ | TUMBLE_START(rowtime(), INTERVAL '1' DAY) as wStart,
+ | SUM(amount)
+ | FROM Orders
+ | GROUP BY TUMBLE(rowtime(), INTERVAL '1' DAY), user
+ """.stripMargin)
+
+// compute SUM(amount) per day (in processing-time)
+val result2 = tableEnv.sql(
+ "SELECT user, SUM(amount) FROM Orders GROUP BY TUMBLE(proctime(), INTERVAL '1' DAY), user")
+
+// compute every hour the SUM(amount) of the last 24 hours in event-time
+val result3 = tableEnv.sql(
+ "SELECT product, SUM(amount) FROM Orders GROUP BY HOP(rowtime(), INTERVAL '1' HOUR, INTERVAL '1' DAY), product")
+
+// compute SUM(amount) per session with 12 hour inactivity gap (in event-time)
+val result4 = tableEnv.sql(
+ """
+ |SELECT
+ | user,
+ | SESSION_START(rowtime(), INTERVAL '12' HOUR) AS sStart,
+ | SESSION_END(rowtime(), INTERVAL '12' HOUR) AS sEnd,
+ | SUM(amount)
+ | FROM Orders
+ | GROUP BY SESSION(rowtime(), INTERVAL '12' HOUR), user
+ """.stripMargin)
+
+{% endhighlight %}
+</div>
+</div>
+
+{% top %}
+
+### Limitations
+
+**TODO: Integrate this with the examples**
+
+#### Batch
+
+The current version supports selection (filter), projection, inner equi-joins, grouping, aggregates, and sorting on batch tables.
+
+Among others, the following SQL features are not supported, yet:
+
+- Timestamps and intervals are limited to milliseconds precision
+- Interval arithmetic is currenly limited
+- Non-equi joins and Cartesian products
+- Efficient grouping sets
+
+*Note: Tables are joined in the order in which they are specified in the `FROM` clause. In some cases the table order must be manually tweaked to resolve Cartesian products.*
+
+#### Streaming
+
+Joins, set operations, and non-windowed aggregations are not supported yet.
+`UNNEST` supports only arrays and does not support `WITH ORDINALITY` yet.
+
+Data Types
+----------
+
+The SQL runtime is built on top of Flink's DataSet and DataStream APIs. Internally, it also uses Flink's `TypeInformation` to distinguish between types. The SQL support does not include all Flink types so far. All supported simple types are listed in `org.apache.flink.table.api.Types`. The following table summarizes the relation between SQL Types, Table API types, and the resulting Java class.
+
+| Table API | SQL | Java type |
+| :--------------------- | :-------------------------- | :--------------------- |
+| `Types.STRING` | `VARCHAR` | `java.lang.String` |
+| `Types.BOOLEAN` | `BOOLEAN` | `java.lang.Boolean` |
+| `Types.BYTE` | `TINYINT` | `java.lang.Byte` |
+| `Types.SHORT` | `SMALLINT` | `java.lang.Short` |
+| `Types.INT` | `INTEGER, INT` | `java.lang.Integer` |
+| `Types.LONG` | `BIGINT` | `java.lang.Long` |
+| `Types.FLOAT` | `REAL, FLOAT` | `java.lang.Float` |
+| `Types.DOUBLE` | `DOUBLE` | `java.lang.Double` |
+| `Types.DECIMAL` | `DECIMAL` | `java.math.BigDecimal` |
+| `Types.DATE` | `DATE` | `java.sql.Date` |
+| `Types.TIME` | `TIME` | `java.sql.Time` |
+| `Types.TIMESTAMP` | `TIMESTAMP(3)` | `java.sql.Timestamp` |
+| `Types.INTERVAL_MONTHS`| `INTERVAL YEAR TO MONTH` | `java.lang.Integer` |
+| `Types.INTERVAL_MILLIS`| `INTERVAL DAY TO SECOND(3)` | `java.lang.Long` |
+| `Types.PRIMITIVE_ARRAY`| `ARRAY` | e.g. `int[]` |
+| `Types.OBJECT_ARRAY` | `ARRAY` | e.g. `java.lang.Byte[]`|
+| `Types.MAP` | `MAP` | `java.util.HashMap` |
+
+
+Advanced types such as generic types, composite types (e.g. POJOs or Tuples), and array types (object or primitive arrays) can be fields of a row.
+
+Generic types are treated as a black box within Table API and SQL yet.
+
+Composite types, however, are fully supported types where fields of a composite type can be accessed using the `.get()` operator in Table API and dot operator (e.g. `MyTable.pojoColumn.myField`) in SQL. Composite types can also be flattened using `.flatten()` in Table API or `MyTable.pojoColumn.*` in SQL.
+
+Array types can be accessed using the `myArray.at(1)` operator in Table API and `myArray[1]` operator in SQL. Array literals can be created using `array(1, 2, 3)` in Table API and `ARRAY[1, 2, 3]` in SQL.
+
+{% top %}
+
+Built-In Functions
+------------------
+
+Both the Table API and SQL come with a set of built-in functions for data transformations. This section gives a brief overview of the available functions so far.
+
+<!--
+This list of SQL functions should be kept in sync with SqlExpressionTest to reduce confusion due to the large amount of SQL functions.
+The documentation is split up and ordered like the tests in SqlExpressionTest.
+-->
+
+The Flink SQL functions (including their syntax) are a subset of Apache Calcite's built-in functions. Most of the documentation has been adopted from the [Calcite SQL reference](https://calcite.apache.org/docs/reference.html).
+
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Comparison functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+value1 = value2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Equals.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 <> value2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Not equal.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 > value2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Greater than.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 >= value2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Greater than or equal.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 < value2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Less than.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 <= value2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Less than or equal.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value IS NULL
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>value</i> is null.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value IS NOT NULL
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>value</i> is not null.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 IS DISTINCT FROM value2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if two values are not equal, treating null values as the same.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 IS NOT DISTINCT FROM value2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if two values are equal, treating null values as the same.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 BETWEEN [ASYMMETRIC | SYMMETRIC] value2 AND value3
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>value1</i> is greater than or equal to <i>value2</i> and less than or equal to <i>value3</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value1 NOT BETWEEN value2 AND value3
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>value1</i> is less than <i>value2</i> or greater than <i>value3</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+string1 LIKE string2 [ ESCAPE string3 ]
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>string1</i> matches pattern <i>string2</i>. An escape character can be defined if necessary.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+string1 NOT LIKE string2 [ ESCAPE string3 ]
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>string1</i> does not match pattern <i>string2</i>. An escape character can be defined if necessary.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+string1 SIMILAR TO string2 [ ESCAPE string3 ]
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>string1</i> matches regular expression <i>string2</i>. An escape character can be defined if necessary.</p>
+ </td>
+ </tr>
+
+
+ <tr>
+ <td>
+ {% highlight text %}
+string1 NOT SIMILAR TO string2 [ ESCAPE string3 ]
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>string1</i> does not match regular expression <i>string2</i>. An escape character can be defined if necessary.</p>
+ </td>
+ </tr>
+
+
+ <tr>
+ <td>
+ {% highlight text %}
+value IN (value [, value]* )
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>value</i> is equal to a value in a list.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value NOT IN (value [, value]* )
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>value</i> is not equal to every value in a list.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+EXISTS (sub-query)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>sub-query</i> returns at least one row. Only supported if the operation can be rewritten in a join and group operation.</p>
+ </td>
+ </tr>
+
+<!-- NOT SUPPORTED SO FAR
+ <tr>
+ <td>
+ {% highlight text %}
+value IN (sub-query)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>value</i> is equal to a row returned by sub-query.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+value NOT IN (sub-query)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>value</i> is not equal to every row returned by sub-query.</p>
+ </td>
+ </tr>
+ -->
+
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Logical functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+boolean1 OR boolean2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean1</i> is TRUE or <i>boolean2</i> is TRUE. Supports three-valued logic.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+boolean1 AND boolean2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean1</i> and <i>boolean2</i> are both TRUE. Supports three-valued logic.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+NOT boolean
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean</i> is not TRUE; returns UNKNOWN if <i>boolean</i> is UNKNOWN.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+boolean IS FALSE
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean</i> is FALSE; returns FALSE if <i>boolean</i> is UNKNOWN.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+boolean IS NOT FALSE
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean</i> is not FALSE; returns TRUE if <i>boolean</i> is UNKNOWN.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+boolean IS TRUE
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean</i> is TRUE; returns FALSE if <i>boolean</i> is UNKNOWN.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+boolean IS NOT TRUE
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean</i> is not TRUE; returns TRUE if <i>boolean</i> is UNKNOWN.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+boolean IS UNKNOWN
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean</i> is UNKNOWN.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+boolean IS NOT UNKNOWN
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns TRUE if <i>boolean</i> is not UNKNOWN.</p>
+ </td>
+ </tr>
+
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Arithmetic functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
++ numeric
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+- numeric
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns negative <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+numeric1 + numeric2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns <i>numeric1</i> plus <i>numeric2</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+numeric1 - numeric2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns <i>numeric1</i> minus <i>numeric2</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+numeric1 * numeric2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns <i>numeric1</i> multiplied by <i>numeric2</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+numeric1 / numeric2
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns <i>numeric1</i> divided by <i>numeric2</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+POWER(numeric1, numeric2)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns <i>numeric1</i> raised to the power of <i>numeric2</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+ABS(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the absolute value of <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+MOD(numeric1, numeric2)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the remainder (modulus) of <i>numeric1</i> divided by <i>numeric2</i>. The result is negative only if <i>numeric1</i> is negative.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+SQRT(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the square root of <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+LN(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the natural logarithm (base e) of <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+LOG10(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the base 10 logarithm of <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+EXP(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns e raised to the power of <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+CEIL(numeric)
+CEILING(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Rounds <i>numeric</i> up, and returns the smallest number that is greater than or equal to <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+FLOOR(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Rounds <i>numeric</i> down, and returns the largest number that is less than or equal to <i>numeric</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+SIN(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Calculates the sine of a given number.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+COS(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Calculates the cosine of a given number.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+TAN(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Calculates the tangent of a given number.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+COT(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Calculates the cotangent of a given number.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+ASIN(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Calculates the arc sine of a given number.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+ACOS(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Calculates the arc cosine of a given number.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+ATAN(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Calculates the arc tangent of a given number.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+DEGREES(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Converts <i>numeric</i> from radians to degrees.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+RADIANS(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Converts <i>numeric</i> from degrees to radians.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+SIGN(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Calculates the signum of a given number.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+ROUND(numeric, int)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Rounds the given number to <i>integer</i> places right to the decimal point.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+PI()
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns a value that is closer than any other value to pi.</p>
+ </td>
+ </tr>
+
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">String functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+string || string
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Concatenates two character strings.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+CHAR_LENGTH(string)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the number of characters in a character string.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+CHARACTER_LENGTH(string)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>As CHAR_LENGTH(<i>string</i>).</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+UPPER(string)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns a character string converted to upper case.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+LOWER(string)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns a character string converted to lower case.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+POSITION(string1 IN string2)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the position of the first occurrence of <i>string1</i> in <i>string2</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+TRIM( { BOTH | LEADING | TRAILING } string1 FROM string2)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Removes leading and/or trailing characters from <i>string2</i>. By default, whitespaces at both sides are removed.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+OVERLAY(string1 PLACING string2 FROM integer [ FOR integer2 ])
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Replaces a substring of <i>string1</i> with <i>string2</i>.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+SUBSTRING(string FROM integer)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns a substring of a character string starting at a given point.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+SUBSTRING(string FROM integer FOR integer)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns a substring of a character string starting at a given point with a given length.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+INITCAP(string)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns string with the first letter of each word converter to upper case and the rest to lower case. Words are sequences of alphanumeric characters separated by non-alphanumeric characters.</p>
+ </td>
+ </tr>
+
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Conditional functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+CASE value
+WHEN value1 [, value11 ]* THEN result1
+[ WHEN valueN [, valueN1 ]* THEN resultN ]*
+[ ELSE resultZ ]
+END
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Simple case.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+CASE
+WHEN condition1 THEN result1
+[ WHEN conditionN THEN resultN ]*
+[ ELSE resultZ ]
+END
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Searched case.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+NULLIF(value, value)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns NULL if the values are the same. For example, <code>NULLIF(5, 5)</code> returns NULL; <code>NULLIF(5, 0)</code> returns 5.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+COALESCE(value, value [, value ]* )
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Provides a value if the first value is null. For example, <code>COALESCE(NULL, 5)</code> returns 5.</p>
+ </td>
+ </tr>
+
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Type conversion functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+CAST(value AS type)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Converts a value to a given type.</p>
+ </td>
+ </tr>
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Value constructor functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <!-- Disabled temporarily in favor of composite type support
+ <tr>
+ <td>
+ {% highlight text %}
+ROW (value [, value]* )
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Creates a row from a list of values.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+(value [, value]* )
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Creates a row from a list of values.</p>
+ </td>
+ </tr>
+-->
+
+ <tr>
+ <td>
+ {% highlight text %}
+array ‘[’ index ‘]’
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the element at a particular position in an array. The index starts at 1.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+ARRAY ‘[’ value [, value ]* ‘]’
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Creates an array from a list of values.</p>
+ </td>
+ </tr>
+
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Temporal functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+DATE string
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Parses a date string in the form "yy-mm-dd" to a SQL date.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+TIME string
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Parses a time <i>string</i> in the form "hh:mm:ss" to a SQL time.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+TIMESTAMP string
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Parses a timestamp <i>string</i> in the form "yy-mm-dd hh:mm:ss.fff" to a SQL timestamp.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+INTERVAL string range
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Parses an interval <i>string</i> in the form "dd hh:mm:ss.fff" for SQL intervals of milliseconds or "yyyy-mm" for SQL intervals of months. An interval range might be e.g. <code>DAY</code>, <code>MINUTE</code>, <code>DAY TO HOUR</code>, or <code>DAY TO SECOND</code> for intervals of milliseconds; <code>YEAR</code> or <code>YEAR TO MONTH</code> for intervals of months. E.g. <code>INTERVAL '10 00:00:00.004' DAY TO SECOND</code>, <code>INTERVAL '10' DAY</code>, or <code>INTERVAL '2-10' YEAR TO MONTH</code> return intervals.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+CURRENT_DATE
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the current SQL date in UTC time zone.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+CURRENT_TIME
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the current SQL time in UTC time zone.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+CURRENT_TIMESTAMP
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the current SQL timestamp in UTC time zone.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+LOCALTIME
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the current SQL time in local time zone.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+LOCALTIMESTAMP
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the current SQL timestamp in local time zone.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+EXTRACT(timeintervalunit FROM temporal)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Extracts parts of a time point or time interval. Returns the part as a long value. E.g. <code>EXTRACT(DAY FROM DATE '2006-06-05')</code> leads to 5.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+FLOOR(timepoint TO timeintervalunit)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Rounds a time point down to the given unit. E.g. <code>FLOOR(TIME '12:44:31' TO MINUTE)</code> leads to 12:44:00.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+CEIL(timepoint TO timeintervalunit)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Rounds a time point up to the given unit. E.g. <code>CEIL(TIME '12:44:31' TO MINUTE)</code> leads to 12:45:00.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+QUARTER(date)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the quarter of a year from a SQL date. E.g. <code>QUARTER(DATE '1994-09-27')</code> leads to 3.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+(timepoint, temporal) OVERLAPS (timepoint, temporal)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Determines whether two anchored time intervals overlap. Time point and temporal are transformed into a range defined by two time points (start, end). The function evaluates <code>leftEnd >= rightStart && rightEnd >= leftStart</code>. E.g. <code>(TIME '2:55:00', INTERVAL '1' HOUR) OVERLAPS (TIME '3:30:00', INTERVAL '2' HOUR)</code> leads to true; <code>(TIME '9:00:00', TIME '10:00:00') OVERLAPS (TIME '10:15:00', INTERVAL '3' HOUR)</code> leads to false.</p>
+ </td>
+ </tr>
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Aggregate functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+COUNT(value [, value]* )
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the number of input rows for which <i>value</i> is not null.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+COUNT(*)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the number of input rows.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+AVG(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the average (arithmetic mean) of <i>numeric</i> across all input values.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+SUM(numeric)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the sum of <i>numeric</i> across all input values.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+MAX(value)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the maximum value of <i>value</i> across all input values.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+MIN(value)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the minimum value of <i>value</i> across all input values.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>
+ {% highlight text %}
+STDDEV_POP(value)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the population standard deviation of the numeric field across all input values.</p>
+ </td>
+ </tr>
+
+<tr>
+ <td>
+ {% highlight text %}
+STDDEV_SAMP(value)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the sample standard deviation of the numeric field across all input values.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+VAR_POP(value)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the population variance (square of the population standard deviation) of the numeric field across all input values.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+VAR_SAMP(value)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the sample variance (square of the sample standard deviation) of the numeric field across all input values.</p>
+ </td>
+ </tr>
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Grouping functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+GROUP_ID()
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns an integer that uniquely identifies the combination of grouping keys.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+GROUPING(expression)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns 1 if <i>expression</i> is rolled up in the current row’s grouping set, 0 otherwise.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+GROUPING_ID(expression [, expression]* )
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns a bit vector of the given grouping expressions.</p>
+ </td>
+ </tr>
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Value access functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+tableName.compositeType.field
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Accesses the field of a Flink composite type (such as Tuple, POJO, etc.) by name and returns it's value.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+tableName.compositeType.*
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Converts a Flink composite type (such as Tuple, POJO, etc.) and all of its direct subtypes into a flat representation where every subtype is a separate field.</p>
+ </td>
+ </tr>
+ </tbody>
+</table>
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 40%">Array functions</th>
+ <th class="text-center">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td>
+ {% highlight text %}
+CARDINALITY(ARRAY)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the number of elements of an array.</p>
+ </td>
+ </tr>
+
+ <tr>
+ <td>
+ {% highlight text %}
+ELEMENT(ARRAY)
+{% endhighlight %}
+ </td>
+ <td>
+ <p>Returns the sole element of an array with a single element. Returns <code>null</code> if the array is empty. Throws an exception if the array has more than one element.</p>
+ </td>
+ </tr>
+ </tbody>
+</table>
+
+### Limitations
+
+The following operations are not supported yet:
+
+- Binary string operators and functions
+- System functions
+- Collection functions
+- Aggregate functions like STDDEV_xxx, VAR_xxx, and REGR_xxx
+- Distinct aggregate functions like COUNT DISTINCT
+
+{% top %}
+
+Reserved Keywords
+-----------------
+
+Although not every SQL feature is implemented yet, some string combinations are already reserved as keywords for future use. If you want to use one of the following strings as a field name, make sure to surround them with backticks (e.g. `` `value` ``, `` `count` ``).
+
+{% highlight sql %}
+
+A, ABS, ABSOLUTE, ACTION, ADA, ADD, ADMIN, AFTER, ALL, ALLOCATE, ALLOW, ALTER, ALWAYS, AND, ANY, ARE, ARRAY, AS, ASC, ASENSITIVE, ASSERTION, ASSIGNMENT, ASYMMETRIC, AT, ATOMIC, ATTRIBUTE, ATTRIBUTES, AUTHORIZATION, AVG, BEFORE, BEGIN, BERNOULLI, BETWEEN, BIGINT, BINARY, BIT, BLOB, BOOLEAN, BOTH, BREADTH, BY, C, CALL, CALLED, CARDINALITY, CASCADE, CASCADED, CASE, CAST, CATALOG, CATALOG_NAME, CEIL, CEILING, CENTURY, CHAIN, CHAR, CHARACTER, CHARACTERISTICTS, CHARACTERS, CHARACTER_LENGTH, CHARACTER_SET_CATALOG, CHARACTER_SET_NAME, CHARACTER_SET_SCHEMA, CHAR_LENGTH, CHECK, CLASS_ORIGIN, CLOB, CLOSE, COALESCE, COBOL, COLLATE, COLLATION, COLLATION_CATALOG, COLLATION_NAME, COLLATION_SCHEMA, COLLECT, COLUMN, COLUMN_NAME, COMMAND_FUNCTION, COMMAND_FUNCTION_CODE, COMMIT, COMMITTED, CONDITION, CONDITION_NUMBER, CONNECT, CONNECTION, CONNECTION_NAME, CONSTRAINT, CONSTRAINTS, CONSTRAINT_CATALOG, CONSTRAINT_NAME, CONSTRAINT_SCHEMA, CONSTRUCTOR, CONTAINS, CONTINUE, CONVERT, CORR, CORRESPONDING, COUN
T, COVAR_POP, COVAR_SAMP, CREATE, CROSS, CUBE, CUME_DIST, CURRENT, CURRENT_CATALOG, CURRENT_DATE, CURRENT_DEFAULT_TRANSFORM_GROUP, CURRENT_PATH, CURRENT_ROLE, CURRENT_SCHEMA, CURRENT_TIME, CURRENT_TIMESTAMP, CURRENT_TRANSFORM_GROUP_FOR_TYPE, CURRENT_USER, CURSOR, CURSOR_NAME, CYCLE, DATA, DATABASE, DATE, DATETIME_INTERVAL_CODE, DATETIME_INTERVAL_PRECISION, DAY, DEALLOCATE, DEC, DECADE, DECIMAL, DECLARE, DEFAULT, DEFAULTS, DEFERRABLE, DEFERRED, DEFINED, DEFINER, DEGREE, DELETE, DENSE_RANK, DEPTH, DEREF, DERIVED, DESC, DESCRIBE, DESCRIPTION, DESCRIPTOR, DETERMINISTIC, DIAGNOSTICS, DISALLOW, DISCONNECT, DISPATCH, DISTINCT, DOMAIN, DOUBLE, DOW, DOY, DROP, DYNAMIC, DYNAMIC_FUNCTION, DYNAMIC_FUNCTION_CODE, EACH, ELEMENT, ELSE, END, END-EXEC, EPOCH, EQUALS, ESCAPE, EVERY, EXCEPT, EXCEPTION, EXCLUDE, EXCLUDING, EXEC, EXECUTE, EXISTS, EXP, EXPLAIN, EXTEND, EXTERNAL, EXTRACT, FALSE, FETCH, FILTER, FINAL, FIRST, FIRST_VALUE, FLOAT, FLOOR, FOLLOWING, FOR, FOREIGN, FORTRAN, FOUND, FRAC_SECOND, F
REE, FROM, FULL, FUNCTION, FUSION, G, GENERAL, GENERATED, GET, GLOBAL, GO, GOTO, GRANT, GRANTED, GROUP, GROUPING, HAVING, HIERARCHY, HOLD, HOUR, IDENTITY, IMMEDIATE, IMPLEMENTATION, IMPORT, IN, INCLUDING, INCREMENT, INDICATOR, INITIALLY, INNER, INOUT, INPUT, INSENSITIVE, INSERT, INSTANCE, INSTANTIABLE, INT, INTEGER, INTERSECT, INTERSECTION, INTERVAL, INTO, INVOKER, IS, ISOLATION, JAVA, JOIN, K, KEY, KEY_MEMBER, KEY_TYPE, LABEL, LANGUAGE, LARGE, LAST, LAST_VALUE, LATERAL, LEADING, LEFT, LENGTH, LEVEL, LIBRARY, LIKE, LIMIT, LN, LOCAL, LOCALTIME, LOCALTIMESTAMP, LOCATOR, LOWER, M, MAP, MATCH, MATCHED, MAX, MAXVALUE, MEMBER, MERGE, MESSAGE_LENGTH, MESSAGE_OCTET_LENGTH, MESSAGE_TEXT, METHOD, MICROSECOND, MILLENNIUM, MIN, MINUTE, MINVALUE, MOD, MODIFIES, MODULE, MONTH, MORE, MULTISET, MUMPS, NAME, NAMES, NATIONAL, NATURAL, NCHAR, NCLOB, NESTING, NEW, NEXT, NO, NONE, NORMALIZE, NORMALIZED, NOT, NULL, NULLABLE, NULLIF, NULLS, NUMBER, NUMERIC, OBJECT, OCTETS, OCTET_LENGTH, OF, OFFSET, OLD, O
N, ONLY, OPEN, OPTION, OPTIONS, OR, ORDER, ORDERING, ORDINALITY, OTHERS, OUT, OUTER, OUTPUT, OVER, OVERLAPS, OVERLAY, OVERRIDING, PAD, PARAMETER, PARAMETER_MODE, PARAMETER_NAME, PARAMETER_ORDINAL_POSITION, PARAMETER_SPECIFIC_CATALOG, PARAMETER_SPECIFIC_NAME, PARAMETER_SPECIFIC_SCHEMA, PARTIAL, PARTITION, PASCAL, PASSTHROUGH, PATH, PERCENTILE_CONT, PERCENTILE_DISC, PERCENT_RANK, PLACING, PLAN, PLI, POSITION, POWER, PRECEDING, PRECISION, PREPARE, PRESERVE, PRIMARY, PRIOR, PRIVILEGES, PROCEDURE, PUBLIC, QUARTER, RANGE, RANK, READ, READS, REAL, RECURSIVE, REF, REFERENCES, REFERENCING, REGR_AVGX, REGR_AVGY, REGR_COUNT, REGR_INTERCEPT, REGR_R2, REGR_SLOPE, REGR_SXX, REGR_SXY, REGR_SYY, RELATIVE, RELEASE, REPEATABLE, RESET, RESTART, RESTRICT, RESULT, RETURN, RETURNED_CARDINALITY, RETURNED_LENGTH, RETURNED_OCTET_LENGTH, RETURNED_SQLSTATE, RETURNS, REVOKE, RIGHT, ROLE, ROLLBACK, ROLLUP, ROUTINE, ROUTINE_CATALOG, ROUTINE_NAME, ROUTINE_SCHEMA, ROW, ROWS, ROW_COUNT, ROW_NUMBER, SAVEPOINT, SCALE
, SCHEMA, SCHEMA_NAME, SCOPE, SCOPE_CATALOGS, SCOPE_NAME, SCOPE_SCHEMA, SCROLL, SEARCH, SECOND, SECTION, SECURITY, SELECT, SELF, SENSITIVE, SEQUENCE, SERIALIZABLE, SERVER, SERVER_NAME, SESSION, SESSION_USER, SET, SETS, SIMILAR, SIMPLE, SIZE, SMALLINT, SOME, SOURCE, SPACE, SPECIFIC, SPECIFICTYPE, SPECIFIC_NAME, SQL, SQLEXCEPTION, SQLSTATE, SQLWARNING, SQL_TSI_DAY, SQL_TSI_FRAC_SECOND, SQL_TSI_HOUR, SQL_TSI_MICROSECOND, SQL_TSI_MINUTE, SQL_TSI_MONTH, SQL_TSI_QUARTER, SQL_TSI_SECOND, SQL_TSI_WEEK, SQL_TSI_YEAR, SQRT, START, STATE, STATEMENT, STATIC, STDDEV_POP, STDDEV_SAMP, STREAM, STRUCTURE, STYLE, SUBCLASS_ORIGIN, SUBMULTISET, SUBSTITUTE, SUBSTRING, SUM, SYMMETRIC, SYSTEM, SYSTEM_USER, TABLE, TABLESAMPLE, TABLE_NAME, TEMPORARY, THEN, TIES, TIME, TIMESTAMP, TIMESTAMPADD, TIMESTAMPDIFF, TIMEZONE_HOUR, TIMEZONE_MINUTE, TINYINT, TO, TOP_LEVEL_COUNT, TRAILING, TRANSACTION, TRANSACTIONS_ACTIVE, TRANSACTIONS_COMMITTED, TRANSACTIONS_ROLLED_BACK, TRANSFORM, TRANSFORMS, TRANSLATE, TRANSLATION,
TREAT, TRIGGER, TRIGGER_CATALOG, TRIGGER_NAME, TRIGGER_SCHEMA, TRIM, TRUE, TYPE, UESCAPE, UNBOUNDED, UNCOMMITTED, UNDER, UNION, UNIQUE, UNKNOWN, UNNAMED, UNNEST, UPDATE, UPPER, UPSERT, USAGE, USER, USER_DEFINED_TYPE_CATALOG, USER_DEFINED_TYPE_CODE, USER_DEFINED_TYPE_NAME, USER_DEFINED_TYPE_SCHEMA, USING, VALUE, VALUES, VARBINARY, VARCHAR, VARYING, VAR_POP, VAR_SAMP, VERSION, VIEW, WEEK, WHEN, WHENEVER, WHERE, WIDTH_BUCKET, WINDOW, WITH, WITHIN, WITHOUT, WORK, WRAPPER, WRITE, XML, YEAR, ZONE
+
+{% endhighlight %}
+
+{% top %}
+
http://git-wip-us.apache.org/repos/asf/flink/blob/a5d93a56/docs/dev/table/streaming.md
----------------------------------------------------------------------
diff --git a/docs/dev/table/streaming.md b/docs/dev/table/streaming.md
new file mode 100644
index 0000000..9699507
--- /dev/null
+++ b/docs/dev/table/streaming.md
@@ -0,0 +1,67 @@
+---
+title: "Streaming Concepts"
+nav-parent_id: tableapi
+nav-pos: 10
+---
+<!--
+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.
+-->
+
+**TODO: has to be completely written**
+
+* This will be replaced by the TOC
+{:toc}
+
+Dynamic table
+-------------
+
+* Stream -> Table
+* Table -> Stream
+* update changes / retraction
+
+{% top %}
+
+Time Attributes
+---------------
+
+### Event-time
+
+* DataStream: Timestamps & WMs required, `.rowtime` (replace attribute or extend schema)
+* TableSource: Timestamps & WMs & DefinedRowtimeAttribute
+
+{% top %}
+
+### Processing time
+
+* DataStream: `.proctime` (only extend schema)
+* TableSource: DefinedProctimeAttribute
+
+{% top %}
+
+Query Configuration
+-------------------
+
+In stream processing, compuations are constantly happening and there are many use cases that require to update previously emitted results. There are many ways in which a query can compute and emit updates. These do not affect the semantics of the query but might lead to approximated results.
+
+Flink's Table API and SQL interface use a `QueryConfig` to control the computation and emission of results and updates.
+
+### State Retention
+
+{% top %}
+
+