Concepts & Common API

// create a TableEnvironment for specific planner batch or streaming
TableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// create a Table
tableEnv.connect(...).createTemporaryTable("table1");
// register an output Table
tableEnv.connect(...).createTemporaryTable("outputTable");

// create a Table object from a Table API query
Table tapiResult = tableEnv.from("table1").select(...);
// create a Table object from a SQL query
Table sqlResult  = tableEnv.sqlQuery("SELECT ... FROM table1 ... ");

// emit a Table API result Table to a TableSink, same for SQL result
TableResult tableResult = tapiResult.executeInsert("outputTable");
tableResult...

// create a TableEnvironment for specific planner batch or streaming
val tableEnv = ... // see "Create a TableEnvironment" section

// create a Table
tableEnv.connect(...).createTemporaryTable("table1")
// register an output Table
tableEnv.connect(...).createTemporaryTable("outputTable")

// create a Table from a Table API query
val tapiResult = tableEnv.from("table1").select(...)
// create a Table from a SQL query
val sqlResult  = tableEnv.sqlQuery("SELECT ... FROM table1 ...")

// emit a Table API result Table to a TableSink, same for SQL result
val tableResult = tapiResult.executeInsert("outputTable")
tableResult...

# create a TableEnvironment for specific planner batch or streaming
table_env = ... # see "Create a TableEnvironment" section

# register a Table
table_env.connect(...).create_temporary_table("table1")

# register an output Table
table_env.connect(...).create_temporary_table("outputTable")

# create a Table from a Table API query
tapi_result = table_env.from_path("table1").select(...)
# create a Table from a SQL query
sql_result  = table_env.sql_query("SELECT ... FROM table1 ...")

# emit a Table API result Table to a TableSink, same for SQL result
table_result = tapi_result.execute_insert("outputTable")
table_result...

// **********************
// FLINK STREAMING QUERY
// **********************
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

EnvironmentSettings fsSettings = EnvironmentSettings.newInstance().useOldPlanner().inStreamingMode().build();
StreamExecutionEnvironment fsEnv = StreamExecutionEnvironment.getExecutionEnvironment();
StreamTableEnvironment fsTableEnv = StreamTableEnvironment.create(fsEnv, fsSettings);
// or TableEnvironment fsTableEnv = TableEnvironment.create(fsSettings);

// ******************
// FLINK BATCH QUERY
// ******************
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.table.api.bridge.java.BatchTableEnvironment;

ExecutionEnvironment fbEnv = ExecutionEnvironment.getExecutionEnvironment();
BatchTableEnvironment fbTableEnv = BatchTableEnvironment.create(fbEnv);

// **********************
// BLINK STREAMING QUERY
// **********************
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

StreamExecutionEnvironment bsEnv = StreamExecutionEnvironment.getExecutionEnvironment();
EnvironmentSettings bsSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build();
StreamTableEnvironment bsTableEnv = StreamTableEnvironment.create(bsEnv, bsSettings);
// or TableEnvironment bsTableEnv = TableEnvironment.create(bsSettings);

// ******************
// BLINK BATCH QUERY
// ******************
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.TableEnvironment;

EnvironmentSettings bbSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inBatchMode().build();
TableEnvironment bbTableEnv = TableEnvironment.create(bbSettings);

// **********************
// FLINK STREAMING QUERY
// **********************
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.table.api.EnvironmentSettings
import org.apache.flink.table.api.bridge.scala.StreamTableEnvironment

val fsSettings = EnvironmentSettings.newInstance().useOldPlanner().inStreamingMode().build()
val fsEnv = StreamExecutionEnvironment.getExecutionEnvironment
val fsTableEnv = StreamTableEnvironment.create(fsEnv, fsSettings)
// or val fsTableEnv = TableEnvironment.create(fsSettings)

// ******************
// FLINK BATCH QUERY
// ******************
import org.apache.flink.api.scala.ExecutionEnvironment
import org.apache.flink.table.api.bridge.scala.BatchTableEnvironment

val fbEnv = ExecutionEnvironment.getExecutionEnvironment
val fbTableEnv = BatchTableEnvironment.create(fbEnv)

// **********************
// BLINK STREAMING QUERY
// **********************
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.table.api.EnvironmentSettings
import org.apache.flink.table.api.bridge.scala.StreamTableEnvironment

val bsEnv = StreamExecutionEnvironment.getExecutionEnvironment
val bsSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build()
val bsTableEnv = StreamTableEnvironment.create(bsEnv, bsSettings)
// or val bsTableEnv = TableEnvironment.create(bsSettings)

// ******************
// BLINK BATCH QUERY
// ******************
import org.apache.flink.table.api.{EnvironmentSettings, TableEnvironment}

val bbSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inBatchMode().build()
val bbTableEnv = TableEnvironment.create(bbSettings)

# **********************
# FLINK STREAMING QUERY
# **********************
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.table import StreamTableEnvironment, EnvironmentSettings

f_s_env = StreamExecutionEnvironment.get_execution_environment()
f_s_settings = EnvironmentSettings.new_instance().use_old_planner().in_streaming_mode().build()
f_s_t_env = StreamTableEnvironment.create(f_s_env, environment_settings=f_s_settings)

# ******************
# FLINK BATCH QUERY
# ******************
from pyflink.dataset import ExecutionEnvironment
from pyflink.table import BatchTableEnvironment

f_b_env = ExecutionEnvironment.get_execution_environment()
f_b_t_env = BatchTableEnvironment.create(f_b_env, table_config)

# **********************
# BLINK STREAMING QUERY
# **********************
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.table import StreamTableEnvironment, EnvironmentSettings

b_s_env = StreamExecutionEnvironment.get_execution_environment()
b_s_settings = EnvironmentSettings.new_instance().use_blink_planner().in_streaming_mode().build()
b_s_t_env = StreamTableEnvironment.create(b_s_env, environment_settings=b_s_settings)

# ******************
# BLINK BATCH QUERY
# ******************
from pyflink.table import EnvironmentSettings, BatchTableEnvironment

b_b_settings = EnvironmentSettings.new_instance().use_blink_planner().in_batch_mode().build()
b_b_t_env = BatchTableEnvironment.create(environment_settings=b_b_settings)

// get a TableEnvironment
TableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// table is the result of a simple projection query 
Table projTable = tableEnv.from("X").select(...);

// register the Table projTable as table "projectedTable"
tableEnv.createTemporaryView("projectedTable", projTable);

// get a TableEnvironment
val tableEnv = ... // see "Create a TableEnvironment" section

// table is the result of a simple projection query 
val projTable: Table = tableEnv.from("X").select(...)

// register the Table projTable as table "projectedTable"
tableEnv.createTemporaryView("projectedTable", projTable)

# get a TableEnvironment
table_env = ... # see "Create a TableEnvironment" section

# table is the result of a simple projection query 
proj_table = table_env.from_path("X").select(...)

# register the Table projTable as table "projectedTable"
table_env.register_table("projectedTable", proj_table)

tableEnvironment
  .connect(...)
  .withFormat(...)
  .withSchema(...)
  .inAppendMode()
  .createTemporaryTable("MyTable")

tableEnvironment
  .connect(...)
  .withFormat(...)
  .withSchema(...)
  .inAppendMode()
  .createTemporaryTable("MyTable")

table_environment \
    .connect(...) \
    .with_format(...) \
    .with_schema(...) \
    .in_append_mode() \
    .create_temporary_table("MyTable")

tableEnvironment.executeSql("CREATE [TEMPORARY] TABLE MyTable (...) WITH (...)")

TableEnvironment tEnv = ...;
tEnv.useCatalog("custom_catalog");
tEnv.useDatabase("custom_database");

Table table = ...;

// register the view named 'exampleView' in the catalog named 'custom_catalog'
// in the database named 'custom_database' 
tableEnv.createTemporaryView("exampleView", table);

// register the view named 'exampleView' in the catalog named 'custom_catalog'
// in the database named 'other_database' 
tableEnv.createTemporaryView("other_database.exampleView", table);

// register the view named 'example.View' in the catalog named 'custom_catalog'
// in the database named 'custom_database' 
tableEnv.createTemporaryView("`example.View`", table);

// register the view named 'exampleView' in the catalog named 'other_catalog'
// in the database named 'other_database' 
tableEnv.createTemporaryView("other_catalog.other_database.exampleView", table);

// get a TableEnvironment
val tEnv: TableEnvironment = ...;
tEnv.useCatalog("custom_catalog")
tEnv.useDatabase("custom_database")

val table: Table = ...;

// register the view named 'exampleView' in the catalog named 'custom_catalog'
// in the database named 'custom_database' 
tableEnv.createTemporaryView("exampleView", table)

// register the view named 'exampleView' in the catalog named 'custom_catalog'
// in the database named 'other_database' 
tableEnv.createTemporaryView("other_database.exampleView", table)

// register the view named 'example.View' in the catalog named 'custom_catalog'
// in the database named 'custom_database' 
tableEnv.createTemporaryView("`example.View`", table)

// register the view named 'exampleView' in the catalog named 'other_catalog'
// in the database named 'other_database' 
tableEnv.createTemporaryView("other_catalog.other_database.exampleView", table)

// get a TableEnvironment
TableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// register Orders table

// scan registered Orders table
Table orders = tableEnv.from("Orders");
// compute revenue for all customers from France
Table revenue = orders
  .filter($("cCountry").isEqual("FRANCE"))
  .groupBy($("cID"), $("cName")
  .select($("cID"), $("cName"), $("revenue").sum().as("revSum"));

// emit or convert Table
// execute query

// get a TableEnvironment
val tableEnv = ... // see "Create a TableEnvironment" section

// register Orders table

// scan registered Orders table
val orders = tableEnv.from("Orders")
// compute revenue for all customers from France
val revenue = orders
  .filter($"cCountry" === "FRANCE")
  .groupBy($"cID", $"cName")
  .select($"cID", $"cName", $"revenue".sum AS "revSum")

// emit or convert Table
// execute query

# get a TableEnvironment
table_env = # see "Create a TableEnvironment" section

# register Orders table

# scan registered Orders table
orders = table_env.from_path("Orders")
# compute revenue for all customers from France
revenue = orders \
    .filter(orders.cCountry == 'FRANCE') \
    .group_by(orders.cID, orders.cName) \
    .select(orders.cID, orders.cName, orders.revenue.sum.alias('revSum'))

# emit or convert Table
# execute query

// get a TableEnvironment
TableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// register Orders table

// compute revenue for all customers from France
Table revenue = tableEnv.sqlQuery(
    "SELECT cID, cName, SUM(revenue) AS revSum " +
    "FROM Orders " +
    "WHERE cCountry = 'FRANCE' " +
    "GROUP BY cID, cName"
  );

// emit or convert Table
// execute query

// get a TableEnvironment
val tableEnv = ... // see "Create a TableEnvironment" section

// register Orders table

// compute revenue for all customers from France
val revenue = tableEnv.sqlQuery("""
  |SELECT cID, cName, SUM(revenue) AS revSum
  |FROM Orders
  |WHERE cCountry = 'FRANCE'
  |GROUP BY cID, cName
  """.stripMargin)

// emit or convert Table
// execute query

# get a TableEnvironment
table_env = ... # see "Create a TableEnvironment" section

# register Orders table

# compute revenue for all customers from France
revenue = table_env.sql_query(
    "SELECT cID, cName, SUM(revenue) AS revSum "
    "FROM Orders "
    "WHERE cCountry = 'FRANCE' "
    "GROUP BY cID, cName"
)

# emit or convert Table
# execute query

// get a TableEnvironment
TableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// register "Orders" table
// register "RevenueFrance" output table

// compute revenue for all customers from France and emit to "RevenueFrance"
tableEnv.executeSql(
    "INSERT INTO RevenueFrance " +
    "SELECT cID, cName, SUM(revenue) AS revSum " +
    "FROM Orders " +
    "WHERE cCountry = 'FRANCE' " +
    "GROUP BY cID, cName"
  );

// get a TableEnvironment
val tableEnv = ... // see "Create a TableEnvironment" section

// register "Orders" table
// register "RevenueFrance" output table

// compute revenue for all customers from France and emit to "RevenueFrance"
tableEnv.executeSql("""
  |INSERT INTO RevenueFrance
  |SELECT cID, cName, SUM(revenue) AS revSum
  |FROM Orders
  |WHERE cCountry = 'FRANCE'
  |GROUP BY cID, cName
  """.stripMargin)

# get a TableEnvironment
table_env = ... # see "Create a TableEnvironment" section

# register "Orders" table
# register "RevenueFrance" output table

# compute revenue for all customers from France and emit to "RevenueFrance"
table_env.execute_sql(
    "INSERT INTO RevenueFrance "
    "SELECT cID, cName, SUM(revenue) AS revSum "
    "FROM Orders "
    "WHERE cCountry = 'FRANCE' "
    "GROUP BY cID, cName"
)

// get a TableEnvironment
TableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// create an output Table
final Schema schema = new Schema()
    .field("a", DataTypes.INT())
    .field("b", DataTypes.STRING())
    .field("c", DataTypes.BIGINT());

tableEnv.connect(new FileSystem().path("/path/to/file"))
    .withFormat(new Csv().fieldDelimiter('|').deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("CsvSinkTable");

// compute a result Table using Table API operators and/or SQL queries
Table result = ...

// emit the result Table to the registered TableSink
result.executeInsert("CsvSinkTable");

// get a TableEnvironment
val tableEnv = ... // see "Create a TableEnvironment" section

// create an output Table
val schema = new Schema()
    .field("a", DataTypes.INT())
    .field("b", DataTypes.STRING())
    .field("c", DataTypes.BIGINT())

tableEnv.connect(new FileSystem().path("/path/to/file"))
    .withFormat(new Csv().fieldDelimiter('|').deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("CsvSinkTable")

// compute a result Table using Table API operators and/or SQL queries
val result: Table = ...

// emit the result Table to the registered TableSink
result.executeInsert("CsvSinkTable")

# get a TableEnvironment
table_env = ... # see "Create a TableEnvironment" section

# create a TableSink
table_env.connect(FileSystem().path("/path/to/file")))
    .with_format(Csv()
                 .field_delimiter(',')
                 .deriveSchema())
    .with_schema(Schema()
                 .field("a", DataTypes.INT())
                 .field("b", DataTypes.STRING())
                 .field("c", DataTypes.BIGINT()))
    .create_temporary_table("CsvSinkTable")

# compute a result Table using Table API operators and/or SQL queries
result = ...

# emit the result Table to the registered TableSink
result.execute_insert("CsvSinkTable")

// get StreamTableEnvironment
// registration of a DataSet in a BatchTableEnvironment is equivalent
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

DataStream<Tuple2<Long, String>> stream = ...

// register the DataStream as View "myTable" with fields "f0", "f1"
tableEnv.createTemporaryView("myTable", stream);

// register the DataStream as View "myTable2" with fields "myLong", "myString"
tableEnv.createTemporaryView("myTable2", stream, $("myLong"), $("myString"));

// get TableEnvironment 
// registration of a DataSet is equivalent
val tableEnv: StreamTableEnvironment = ... // see "Create a TableEnvironment" section

val stream: DataStream[(Long, String)] = ...

// register the DataStream as View "myTable" with fields "f0", "f1"
tableEnv.createTemporaryView("myTable", stream)

// register the DataStream as View "myTable2" with fields "myLong", "myString"
tableEnv.createTemporaryView("myTable2", stream, 'myLong, 'myString)

// get StreamTableEnvironment
// registration of a DataSet in a BatchTableEnvironment is equivalent
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

DataStream<Tuple2<Long, String>> stream = ...

// Convert the DataStream into a Table with default fields "f0", "f1"
Table table1 = tableEnv.fromDataStream(stream);

// Convert the DataStream into a Table with fields "myLong", "myString"
Table table2 = tableEnv.fromDataStream(stream, $("myLong"), $("myString"));

// get TableEnvironment
// registration of a DataSet is equivalent
val tableEnv = ... // see "Create a TableEnvironment" section

val stream: DataStream[(Long, String)] = ...

// convert the DataStream into a Table with default fields "_1", "_2"
val table1: Table = tableEnv.fromDataStream(stream)

// convert the DataStream into a Table with fields "myLong", "myString"
val table2: Table = tableEnv.fromDataStream(stream, $"myLong", $"myString")

// get StreamTableEnvironment. 
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// Table with two fields (String name, Integer age)
Table table = ...

// convert the Table into an append DataStream of Row by specifying the class
DataStream<Row> dsRow = tableEnv.toAppendStream(table, Row.class);

// convert the Table into an append DataStream of Tuple2<String, Integer> 
//   via a TypeInformation
TupleTypeInfo<Tuple2<String, Integer>> tupleType = new TupleTypeInfo<>(
  Types.STRING(),
  Types.INT());
DataStream<Tuple2<String, Integer>> dsTuple = 
  tableEnv.toAppendStream(table, tupleType);

// convert the Table into a retract DataStream of Row.
//   A retract stream of type X is a DataStream<Tuple2<Boolean, X>>. 
//   The boolean field indicates the type of the change. 
//   True is INSERT, false is DELETE.
DataStream<Tuple2<Boolean, Row>> retractStream = 
  tableEnv.toRetractStream(table, Row.class);

// get TableEnvironment. 
// registration of a DataSet is equivalent
val tableEnv: StreamTableEnvironment = ... // see "Create a TableEnvironment" section

// Table with two fields (String name, Integer age)
val table: Table = ...

// convert the Table into an append DataStream of Row
val dsRow: DataStream[Row] = tableEnv.toAppendStream[Row](table)

// convert the Table into an append DataStream of Tuple2[String, Int]
val dsTuple: DataStream[(String, Int)] dsTuple = 
  tableEnv.toAppendStream[(String, Int)](table)

// convert the Table into a retract DataStream of Row.
//   A retract stream of type X is a DataStream[(Boolean, X)]. 
//   The boolean field indicates the type of the change. 
//   True is INSERT, false is DELETE.
val retractStream: DataStream[(Boolean, Row)] = tableEnv.toRetractStream[Row](table)

// get BatchTableEnvironment
BatchTableEnvironment tableEnv = BatchTableEnvironment.create(env);

// Table with two fields (String name, Integer age)
Table table = ...

// convert the Table into a DataSet of Row by specifying a class
DataSet<Row> dsRow = tableEnv.toDataSet(table, Row.class);

// convert the Table into a DataSet of Tuple2<String, Integer> via a TypeInformation
TupleTypeInfo<Tuple2<String, Integer>> tupleType = new TupleTypeInfo<>(
  Types.STRING(),
  Types.INT());
DataSet<Tuple2<String, Integer>> dsTuple = 
  tableEnv.toDataSet(table, tupleType);

// get TableEnvironment 
// registration of a DataSet is equivalent
val tableEnv = BatchTableEnvironment.create(env)

// Table with two fields (String name, Integer age)
val table: Table = ...

// convert the Table into a DataSet of Row
val dsRow: DataSet[Row] = tableEnv.toDataSet[Row](table)

// convert the Table into a DataSet of Tuple2[String, Int]
val dsTuple: DataSet[(String, Int)] = tableEnv.toDataSet[(String, Int)](table)

// get a StreamTableEnvironment, works for BatchTableEnvironment equivalently
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section;

DataStream<Tuple2<Long, Integer>> stream = ...

// convert DataStream into Table with default field names "f0" and "f1"
Table table = tableEnv.fromDataStream(stream);

// convert DataStream into Table with field "myLong" only
Table table = tableEnv.fromDataStream(stream, $("myLong"));

// convert DataStream into Table with field names "myLong" and "myInt"
Table table = tableEnv.fromDataStream(stream, $("myLong"), $("myInt"));

// get a TableEnvironment
val tableEnv: StreamTableEnvironment = ... // see "Create a TableEnvironment" section

val stream: DataStream[(Long, Int)] = ...

// convert DataStream into Table with default field names "_1" and "_2"
val table: Table = tableEnv.fromDataStream(stream)

// convert DataStream into Table with field "myLong" only
val table: Table = tableEnv.fromDataStream(stream, $"myLong")

// convert DataStream into Table with field names "myLong" and "myInt"
val table: Table = tableEnv.fromDataStream(stream, $"myLong", $"myInt")

// get a StreamTableEnvironment, works for BatchTableEnvironment equivalently
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

DataStream<Tuple2<Long, Integer>> stream = ...

// convert DataStream into Table with default field names "f0" and "f1"
Table table = tableEnv.fromDataStream(stream);

// convert DataStream into Table with field "f1" only
Table table = tableEnv.fromDataStream(stream, $("f1"));

// convert DataStream into Table with swapped fields
Table table = tableEnv.fromDataStream(stream, $("f1"), $("f0"));

// convert DataStream into Table with swapped fields and field names "myInt" and "myLong"
Table table = tableEnv.fromDataStream(stream, $("f1").as("myInt"), $("f0").as("myLong"));

// get a TableEnvironment
val tableEnv: StreamTableEnvironment = ... // see "Create a TableEnvironment" section

val stream: DataStream[(Long, Int)] = ...

// convert DataStream into Table with default field names "_1" and "_2"
val table: Table = tableEnv.fromDataStream(stream)

// convert DataStream into Table with field "_2" only
val table: Table = tableEnv.fromDataStream(stream, $"_2")

// convert DataStream into Table with swapped fields
val table: Table = tableEnv.fromDataStream(stream, $"_2", $"_1")

// convert DataStream into Table with swapped fields and field names "myInt" and "myLong"
val table: Table = tableEnv.fromDataStream(stream, $"_2" as "myInt", $"_1" as "myLong")

// get a StreamTableEnvironment, works for BatchTableEnvironment equivalently
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

DataStream<Long> stream = ...

// convert DataStream into Table with default field name "f0"
Table table = tableEnv.fromDataStream(stream);

// convert DataStream into Table with field name "myLong"
Table table = tableEnv.fromDataStream(stream, $("myLong"));

// get a TableEnvironment
val tableEnv: StreamTableEnvironment = ... // see "Create a TableEnvironment" section

val stream: DataStream[Long] = ...

// convert DataStream into Table with default field name "f0"
val table: Table = tableEnv.fromDataStream(stream)

// convert DataStream into Table with field name "myLong"
val table: Table = tableEnv.fromDataStream(stream, $"myLong")

// get a StreamTableEnvironment, works for BatchTableEnvironment equivalently
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

DataStream<Tuple2<Long, String>> stream = ...

// convert DataStream into Table with default field names "f0", "f1"
Table table = tableEnv.fromDataStream(stream);

// convert DataStream into Table with renamed field names "myLong", "myString" (position-based)
Table table = tableEnv.fromDataStream(stream, $("myLong"), $("myString"));

// convert DataStream into Table with reordered fields "f1", "f0" (name-based)
Table table = tableEnv.fromDataStream(stream, $("f1"), $("f0"));

// convert DataStream into Table with projected field "f1" (name-based)
Table table = tableEnv.fromDataStream(stream, $("f1"));

// convert DataStream into Table with reordered and aliased fields "myString", "myLong" (name-based)
Table table = tableEnv.fromDataStream(stream, $("f1").as("myString"), $("f0").as("myLong"));

// get a TableEnvironment
val tableEnv: StreamTableEnvironment = ... // see "Create a TableEnvironment" section

val stream: DataStream[(Long, String)] = ...

// convert DataStream into Table with renamed default field names '_1, '_2
val table: Table = tableEnv.fromDataStream(stream)

// convert DataStream into Table with field names "myLong", "myString" (position-based)
val table: Table = tableEnv.fromDataStream(stream, $"myLong", $"myString")

// convert DataStream into Table with reordered fields "_2", "_1" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"_2", $"_1")

// convert DataStream into Table with projected field "_2" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"_2")

// convert DataStream into Table with reordered and aliased fields "myString", "myLong" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"_2" as "myString", $"_1" as "myLong")

// define case class
case class Person(name: String, age: Int)
val streamCC: DataStream[Person] = ...

// convert DataStream into Table with default field names 'name, 'age
val table = tableEnv.fromDataStream(streamCC)

// convert DataStream into Table with field names 'myName, 'myAge (position-based)
val table = tableEnv.fromDataStream(streamCC, $"myName", $"myAge")

// convert DataStream into Table with reordered and aliased fields "myAge", "myName" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"age" as "myAge", $"name" as "myName")

// get a StreamTableEnvironment, works for BatchTableEnvironment equivalently
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// Person is a POJO with fields "name" and "age"
DataStream<Person> stream = ...

// convert DataStream into Table with default field names "age", "name" (fields are ordered by name!)
Table table = tableEnv.fromDataStream(stream);

// convert DataStream into Table with renamed fields "myAge", "myName" (name-based)
Table table = tableEnv.fromDataStream(stream, $("age").as("myAge"), $("name").as("myName"));

// convert DataStream into Table with projected field "name" (name-based)
Table table = tableEnv.fromDataStream(stream, $("name"));

// convert DataStream into Table with projected and renamed field "myName" (name-based)
Table table = tableEnv.fromDataStream(stream, $("name").as("myName"));

// get a TableEnvironment
val tableEnv: StreamTableEnvironment = ... // see "Create a TableEnvironment" section

// Person is a POJO with field names "name" and "age"
val stream: DataStream[Person] = ...

// convert DataStream into Table with default field names "age", "name" (fields are ordered by name!)
val table: Table = tableEnv.fromDataStream(stream)

// convert DataStream into Table with renamed fields "myAge", "myName" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"age" as "myAge", $"name" as "myName")

// convert DataStream into Table with projected field "name" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"name")

// convert DataStream into Table with projected and renamed field "myName" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"name" as "myName")

// get a StreamTableEnvironment, works for BatchTableEnvironment equivalently
StreamTableEnvironment tableEnv = ...; // see "Create a TableEnvironment" section

// DataStream of Row with two fields "name" and "age" specified in `RowTypeInfo`
DataStream<Row> stream = ...

// convert DataStream into Table with default field names "name", "age"
Table table = tableEnv.fromDataStream(stream);

// convert DataStream into Table with renamed field names "myName", "myAge" (position-based)
Table table = tableEnv.fromDataStream(stream, $("myName"), $("myAge"));

// convert DataStream into Table with renamed fields "myName", "myAge" (name-based)
Table table = tableEnv.fromDataStream(stream, $("name").as("myName"), $("age").as("myAge"));

// convert DataStream into Table with projected field "name" (name-based)
Table table = tableEnv.fromDataStream(stream, $("name"));

// convert DataStream into Table with projected and renamed field "myName" (name-based)
Table table = tableEnv.fromDataStream(stream, $("name").as("myName"));

// get a TableEnvironment
val tableEnv: StreamTableEnvironment = ... // see "Create a TableEnvironment" section

// DataStream of Row with two fields "name" and "age" specified in `RowTypeInfo`
val stream: DataStream[Row] = ...

// convert DataStream into Table with default field names "name", "age"
val table: Table = tableEnv.fromDataStream(stream)

// convert DataStream into Table with renamed field names "myName", "myAge" (position-based)
val table: Table = tableEnv.fromDataStream(stream, $"myName", $"myAge")

// convert DataStream into Table with renamed fields "myName", "myAge" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"name" as "myName", $"age" as "myAge")

// convert DataStream into Table with projected field "name" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"name")

// convert DataStream into Table with projected and renamed field "myName" (name-based)
val table: Table = tableEnv.fromDataStream(stream, $"name" as "myName")

StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
StreamTableEnvironment tEnv = StreamTableEnvironment.create(env);

DataStream<Tuple2<Integer, String>> stream1 = env.fromElements(new Tuple2<>(1, "hello"));
DataStream<Tuple2<Integer, String>> stream2 = env.fromElements(new Tuple2<>(1, "hello"));

// explain Table API
Table table1 = tEnv.fromDataStream(stream1, $("count"), $("word"));
Table table2 = tEnv.fromDataStream(stream2, $("count"), $("word"));
Table table = table1
  .where($("word").like("F%"))
  .unionAll(table2);
System.out.println(table.explain());

val env = StreamExecutionEnvironment.getExecutionEnvironment
val tEnv = StreamTableEnvironment.create(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)
println(table.explain())

env = StreamExecutionEnvironment.get_execution_environment()
t_env = StreamTableEnvironment.create(env)

table1 = t_env.from_elements([(1, "hello")], ["count", "word"])
table2 = t_env.from_elements([(1, "hello")], ["count", "word"])
table = table1 \
    .where(table1.word.like('F%')) \
    .union_all(table2)
print(table.explain())

EnvironmentSettings settings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build();
TableEnvironment tEnv = TableEnvironment.create(settings);

final Schema schema = new Schema()
    .field("count", DataTypes.INT())
    .field("word", DataTypes.STRING());

tEnv.connect(new FileSystem().path("/source/path1"))
    .withFormat(new Csv().deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("MySource1");
tEnv.connect(new FileSystem().path("/source/path2"))
    .withFormat(new Csv().deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("MySource2");
tEnv.connect(new FileSystem().path("/sink/path1"))
    .withFormat(new Csv().deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("MySink1");
tEnv.connect(new FileSystem().path("/sink/path2"))
    .withFormat(new Csv().deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("MySink2");
    
StatementSet stmtSet = tEnv.createStatementSet();

Table table1 = tEnv.from("MySource1").where($("word").like("F%"));
stmtSet.addInsert("MySink1", table1);

Table table2 = table1.unionAll(tEnv.from("MySource2"));
stmtSet.addInsert("MySink2", table2);

String explanation = stmtSet.explain();
System.out.println(explanation);

val settings = EnvironmentSettings.newInstance.useBlinkPlanner.inStreamingMode.build
val tEnv = TableEnvironment.create(settings)

val schema = new Schema()
    .field("count", DataTypes.INT())
    .field("word", DataTypes.STRING())

tEnv.connect(new FileSystem().path("/source/path1"))
    .withFormat(new Csv().deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("MySource1")
tEnv.connect(new FileSystem().path("/source/path2"))
    .withFormat(new Csv().deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("MySource2")
tEnv.connect(new FileSystem().path("/sink/path1"))
    .withFormat(new Csv().deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("MySink1")
tEnv.connect(new FileSystem().path("/sink/path2"))
    .withFormat(new Csv().deriveSchema())
    .withSchema(schema)
    .createTemporaryTable("MySink2")
    
val stmtSet = tEnv.createStatementSet()

val table1 = tEnv.from("MySource1").where($"word".like("F%"))
stmtSet.addInsert("MySink1", table1)

val table2 = table1.unionAll(tEnv.from("MySource2"))
stmtSet.addInsert("MySink2", table2)

val explanation = stmtSet.explain()
println(explanation)

settings = EnvironmentSettings.new_instance().use_blink_planner().in_streaming_mode().build()
t_env = TableEnvironment.create(environment_settings=settings)

schema = Schema()
    .field("count", DataTypes.INT())
    .field("word", DataTypes.STRING())

t_env.connect(FileSystem().path("/source/path1")))
    .with_format(Csv().deriveSchema())
    .with_schema(schema)
    .create_temporary_table("MySource1")
t_env.connect(FileSystem().path("/source/path2")))
    .with_format(Csv().deriveSchema())
    .with_schema(schema)
    .create_temporary_table("MySource2")
t_env.connect(FileSystem().path("/sink/path1")))
    .with_format(Csv().deriveSchema())
    .with_schema(schema)
    .create_temporary_table("MySink1")
t_env.connect(FileSystem().path("/sink/path2")))
    .with_format(Csv().deriveSchema())
    .with_schema(schema)
    .create_temporary_table("MySink2")
    
stmt_set = t_env.create_statement_set()

table1 = t_env.from_path("MySource1").where(col('word').like('F%'))
stmt_set.add_insert("MySink1", table1)

table2 = table1.union_all(t_env.from_path("MySource2"))
stmt_set.add_insert("MySink2", table2)

explanation = stmt_set.explain()
print(explanation)