The Table API is a unified, relational API for stream and batch processing. Table API queries can be run on batch or streaming input without modifications. The Table API is a super set of the SQL language and is specially designed for working with Apache Flink. The Table API is a language-integrated API for Scala and Java. Instead of specifying queries as String values as common with SQL, Table API queries are defined in a language-embedded style in Java or Scala with IDE support like autocompletion and syntax validation.
The Table API shares many concepts and parts of its API with Flinkās SQL integration. Have a look at the Common Concepts & API to learn how to register tables or to create a Table
object. The Streaming Concepts page discusses streaming specific concepts such as dynamic tables and time attributes.
The following examples assume a registered table called Orders
with attributes (a, b, c, rowtime)
. The rowtime
field is either a logical time attribute in streaming or a regular timestamp field in batch.
The Table API is available for Scala and Java. The Scala Table API leverages on Scala expressions, the Java Table API is based on strings which are parsed and converted into equivalent expressions.
The following example shows the differences between the Scala and Java Table API. The table program is executed in a batch environment. It scans the Orders
table, groups by field a
, and counts the resulting rows per group. The result of the table program is converted into a DataSet
of type Row
and printed.
The Java Table API is enabled by importing org.apache.flink.table.api.java.*
. The following example shows how a Java Table API program is constructed and how expressions are specified as strings.
// environment configuration
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
BatchTableEnvironment tEnv = TableEnvironment.getTableEnvironment(env);
// register Orders table in table environment
// ...
// specify table program
Table orders = tEnv.scan("Orders"); // schema (a, b, c, rowtime)
Table counts = orders
.groupBy("a")
.select("a, b.count as cnt");
// conversion to DataSet
DataSet<Row> result = tEnv.toDataSet(counts, Row.class);
result.print();
The Scala Table API is enabled by importing org.apache.flink.api.scala._
and org.apache.flink.table.api.scala._
.
The following example shows how a Scala Table API program is constructed. Table attributes are referenced using Scala Symbols, which start with an apostrophe character ('
).
import org.apache.flink.api.scala._
import org.apache.flink.table.api.scala._
// environment configuration
val env = ExecutionEnvironment.getExecutionEnvironment
val tEnv = TableEnvironment.getTableEnvironment(env)
// register Orders table in table environment
// ...
// specify table program
val orders = tEnv.scan("Orders") // schema (a, b, c, rowtime)
val result = orders
.groupBy('a)
.select('a, 'b.count as 'cnt)
.toDataSet[Row] // conversion to DataSet
.print()
The next example shows a more complex Table API program. The program scans again the Orders
table. It filters null values, normalizes the field a
of type String, and calculates for each hour and product a
the average billing amount b
.
// environment configuration
// ...
// specify table program
Table orders = tEnv.scan("Orders"); // schema (a, b, c, rowtime)
Table result = orders
.filter("a.isNotNull && b.isNotNull && c.isNotNull")
.select("a.lowerCase() as a, b, rowtime")
.window(Tumble.over("1.hour").on("rowtime").as("hourlyWindow"))
.groupBy("hourlyWindow, a")
.select("a, hourlyWindow.end as hour, b.avg as avgBillingAmount");
// environment configuration
// ...
// specify table program
val orders: Table = tEnv.scan("Orders") // schema (a, b, c, rowtime)
val result: Table = orders
.filter('a.isNotNull && 'b.isNotNull && 'c.isNotNull)
.select('a.lowerCase() as 'a, 'b, 'rowtime)
.window(Tumble over 1.hour on 'rowtime as 'hourlyWindow)
.groupBy('hourlyWindow, 'a)
.select('a, 'hourlyWindow.end as 'hour, 'b.avg as 'avgBillingAmount)
Since the Table API is a unified API for batch and streaming data, both example programs can be executed on batch and streaming inputs without any modification of the table program itself. In both cases, the program produces the same results given that streaming records are not late (see Streaming Concepts for details).
The Table API supports the following operations. Please note that not all operations are available in both batch and streaming yet; they are tagged accordingly.
Operators | Description |
---|---|
Scan Batch Streaming |
Similar to the FROM clause in a SQL query. Performs a scan of a registered table.
|
Select Batch Streaming |
Similar to a SQL SELECT statement. Performs a select operation.
You can use star (
|
As Batch Streaming |
Renames fields.
|
Where / Filter Batch Streaming |
Similar to a SQL WHERE clause. Filters out rows that do not pass the filter predicate.
|
Operators | Description |
---|---|
Scan Batch Streaming |
Similar to the FROM clause in a SQL query. Performs a scan of a registered table.
|
Select Batch Streaming |
Similar to a SQL SELECT statement. Performs a select operation.
You can use star (
|
As Batch Streaming |
Renames fields.
|
Where / Filter Batch Streaming |
Similar to a SQL WHERE clause. Filters out rows that do not pass the filter predicate.
|
Operators | Description |
---|---|
GroupBy Aggregation Batch Streaming Result Updating |
Similar to a SQL GROUP BY clause. Groups the rows on the grouping keys with a following running aggregation operator to aggregate rows group-wise.
Note: For streaming queries the required state to compute the query result might grow infinitely depending on the type of aggregation and the number of distinct grouping keys. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
GroupBy Window Aggregation Batch Streaming |
Groups and aggregates a table on a group window and possibly one or more grouping keys.
|
Over Window Aggregation Streaming |
Similar to a SQL OVER clause. Over window aggregates are computed for each row, based on a window (range) of preceding and succeeding rows. See the over windows section for more details.
Note: All aggregates must be defined over the same window, i.e., same partitioning, sorting, and range. Currently, only windows with PRECEDING (UNBOUNDED and bounded) to CURRENT ROW range are supported. Ranges with FOLLOWING are not supported yet. ORDER BY must be specified on a single time attribute. |
Distinct Batch Streaming Result Updating |
Similar to a SQL DISTINCT clause. Returns records with distinct value combinations.
Note: For streaming queries the required state to compute the query result might grow infinitely depending on the number of distinct fields. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
Operators | Description |
---|---|
GroupBy Aggregation Batch Streaming Result Updating |
Similar to a SQL GROUP BY clause. Groups the rows on the grouping keys with a following running aggregation operator to aggregate rows group-wise.
Note: For streaming queries the required state to compute the query result might grow infinitely depending on the type of aggregation and the number of distinct grouping keys. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
GroupBy Window Aggregation Batch Streaming |
Groups and aggregates a table on a group window and possibly one or more grouping keys.
|
Over Window Aggregation Streaming |
Similar to a SQL OVER clause. Over window aggregates are computed for each row, based on a window (range) of preceding and succeeding rows. See the over windows section for more details.
Note: All aggregates must be defined over the same window, i.e., same partitioning, sorting, and range. Currently, only windows with PRECEDING (UNBOUNDED and bounded) to CURRENT ROW range are supported. Ranges with FOLLOWING are not supported yet. ORDER BY must be specified on a single time attribute. |
Distinct Batch |
Similar to a SQL DISTINCT clause. Returns records with distinct value combinations.
Note: For streaming queries the required state to compute the query result might grow infinitely depending on the number of distinct fields. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
Operators | Description |
---|---|
Inner Join Batch Streaming |
Similar to a SQL JOIN clause. Joins two tables. Both tables must have distinct field names and at least one equality join predicate must be defined through join operator or using a where or filter operator.
Note: For streaming queries the required state to compute the query result might grow infinitely depending on the number of distinct input rows. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
Outer Join Batch Streaming Result Updating |
Similar to SQL LEFT/RIGHT/FULL OUTER JOIN clauses. Joins two tables. Both tables must have distinct field names and at least one equality join predicate must be defined.
Note: For streaming queries the required state to compute the query result might grow infinitely depending on the number of distinct input rows. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
Time-windowed Join Batch Streaming |
Note: Time-windowed joins are a subset of regular joins that can be processed in a streaming fashion. A time-windowed join requires at least one equi-join predicate and a join condition that bounds the time on both sides. Such a condition can be defined by two appropriate range predicates ( For example, the following predicates are valid window join conditions:
|
Inner Join with Table Function Batch Streaming |
Joins a table with a the results of a table function. Each row of the left (outer) table is joined with all rows produced by the corresponding call of the table function. A row of the left (outer) table is dropped, if its table function call returns an empty result.
|
Left Outer Join with Table Function Batch Streaming |
Joins a table with a the results of a table function. Each row of the left (outer) table is joined with all rows produced by the corresponding call of the table function. If a table function call returns an empty result, the corresponding outer row is preserved and the result padded with null values. Note: Currently, the predicate of a table function left outer join can only be empty or literal
|
Operators | Description |
---|---|
Inner Join Batch Streaming |
Similar to a SQL JOIN clause. Joins two tables. Both tables must have distinct field names and at least one equality join predicate must be defined through join operator or using a where or filter operator.
Note: For streaming queries the required state to compute the query result might grow infinitely depending on the number of distinct input rows. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
Outer Join Batch Streaming Result Updating |
Similar to SQL LEFT/RIGHT/FULL OUTER JOIN clauses. Joins two tables. Both tables must have distinct field names and at least one equality join predicate must be defined.
Note: For streaming queries the required state to compute the query result might grow infinitely depending on the number of distinct input rows. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
Time-windowed Join Batch Streaming |
Note: Time-windowed joins are a subset of regular joins that can be processed in a streaming fashion. A time-windowed join requires at least one equi-join predicate and a join condition that bounds the time on both sides. Such a condition can be defined by two appropriate range predicates ( For example, the following predicates are valid window join conditions:
|
Inner Join with Table Function Batch Streaming |
Joins a table with a the results of a table function. Each row of the left (outer) table is joined with all rows produced by the corresponding call of the table function. A row of the left (outer) table is dropped, if its table function call returns an empty result.
|
Left Outer Join with Table Function Batch Streaming |
Joins a table with a the results of a table function. Each row of the left (outer) table is joined with all rows produced by the corresponding call of the table function. If a table function call returns an empty result, the corresponding outer row is preserved and the result padded with null values. Note: Currently, the predicate of a table function left outer join can only be empty or literal
|
Operators | Description |
---|---|
Union Batch |
Similar to a SQL UNION clause. Unions two tables with duplicate records removed. Both tables must have identical field types.
|
UnionAll Batch Streaming |
Similar to a SQL UNION ALL clause. Unions two tables. Both tables must have identical field types.
|
Intersect Batch |
Similar to a SQL INTERSECT clause. Intersect returns records that exist in both tables. If a record is present one or both tables more than once, it is returned just once, i.e., the resulting table has no duplicate records. Both tables must have identical field types.
|
IntersectAll Batch |
Similar to a SQL INTERSECT ALL clause. IntersectAll returns records that exist in both tables. If a record is present in both tables more than once, it is returned as many times as it is present in both tables, i.e., the resulting table might have duplicate records. Both tables must have identical field types.
|
Minus Batch |
Similar to a SQL EXCEPT clause. Minus returns records from the left table that do not exist in the right table. Duplicate records in the left table are returned exactly once, i.e., duplicates are removed. Both tables must have identical field types.
|
MinusAll Batch |
Similar to a SQL EXCEPT ALL clause. MinusAll returns the records that do not exist in the right table. A record that is present n times in the left table and m times in the right table is returned (n - m) times, i.e., as many duplicates as are present in the right table are removed. Both tables must have identical field types.
|
In Batch Streaming |
Similar to a SQL IN clause. In returns true if an expression exists in a given table sub-query. The sub-query table must consist of one column. This column must have the same data type as the expression.
Note: For streaming queries the operation is rewritten in a join and group operation. The required state to compute the query result might grow infinitely depending on the number of distinct input rows. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
Operators | Description |
---|---|
Union Batch |
Similar to a SQL UNION clause. Unions two tables with duplicate records removed, both tables must have identical field types.
|
UnionAll Batch Streaming |
Similar to a SQL UNION ALL clause. Unions two tables, both tables must have identical field types.
|
Intersect Batch |
Similar to a SQL INTERSECT clause. Intersect returns records that exist in both tables. If a record is present in one or both tables more than once, it is returned just once, i.e., the resulting table has no duplicate records. Both tables must have identical field types.
|
IntersectAll Batch |
Similar to a SQL INTERSECT ALL clause. IntersectAll returns records that exist in both tables. If a record is present in both tables more than once, it is returned as many times as it is present in both tables, i.e., the resulting table might have duplicate records. Both tables must have identical field types.
|
Minus Batch |
Similar to a SQL EXCEPT clause. Minus returns records from the left table that do not exist in the right table. Duplicate records in the left table are returned exactly once, i.e., duplicates are removed. Both tables must have identical field types.
|
MinusAll Batch |
Similar to a SQL EXCEPT ALL clause. MinusAll returns the records that do not exist in the right table. A record that is present n times in the left table and m times in the right table is returned (n - m) times, i.e., as many duplicates as are present in the right table are removed. Both tables must have identical field types.
|
In Batch Streaming |
Similar to a SQL IN clause. In returns true if an expression exists in a given table sub-query. The sub-query table must consist of one column. This column must have the same data type as the expression.
Note: For streaming queries the operation is rewritten in a join and group operation. The required state to compute the query result might grow infinitely depending on the number of distinct input rows. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
Operators | Description |
---|---|
Order By Batch |
Similar to a SQL ORDER BY clause. Returns records globally sorted across all parallel partitions.
|
Offset & Fetch Batch |
Similar to the SQL OFFSET and FETCH clauses. Offset and Fetch limit the number of records returned from a sorted result. Offset and Fetch are technically part of the Order By operator and thus must be preceded by it.
|
Operators | Description |
---|---|
Order By Batch |
Similar to a SQL ORDER BY clause. Returns records globally sorted across all parallel partitions.
|
Offset & Fetch Batch |
Similar to the SQL OFFSET and FETCH clauses. Offset and Fetch limit the number of records returned from a sorted result. Offset and Fetch are technically part of the Order By operator and thus must be preceded by it.
|
Operators | Description |
---|---|
Insert Into Batch Streaming |
Similar to the INSERT INTO clause in a SQL query. Performs a insertion into a registered output table. Output tables must be registered in the TableEnvironment (see Register a TableSink). Moreover, the schema of the registered table must match the schema of the query.
|
Operators | Description |
---|---|
Insert Into Batch Streaming |
Similar to the INSERT INTO clause in a SQL query. Performs a insertion into a registered output table. Output tables must be registered in the TableEnvironment (see Register a TableSink). Moreover, the schema of the registered table must match the schema of the query.
|
Group window aggregates group rows into finite groups based on time or row-count intervals and evaluate aggregation functions once per group. For batch tables, windows are a convenient shortcut to group records by time intervals.
Windows are defined using the window(w: Window)
clause and require an alias, which is specified using the as
clause. In order to group a table by a window, the window alias must be referenced in the groupBy(...)
clause like a regular grouping attribute.
The following example shows how to define a window aggregation on a table.
Table table = input
.window([Window w].as("w")) // define window with alias w
.groupBy("w") // group the table by window w
.select("b.sum"); // aggregate
val table = input
.window([w: Window] as 'w) // define window with alias w
.groupBy('w) // group the table by window w
.select('b.sum) // aggregate
In streaming environments, window aggregates can only be computed in parallel if they group on one or more attributes in addition to the window, i.e., the groupBy(...)
clause references a window alias and at least one additional attribute. A groupBy(...)
clause that only references a window alias (such as in the example above) can only be evaluated by a single, non-parallel task.
The following example shows how to define a window aggregation with additional grouping attributes.
Table table = input
.window([Window w].as("w")) // define window with alias w
.groupBy("w, a") // group the table by attribute a and window w
.select("a, b.sum"); // aggregate
val table = input
.window([w: Window] as 'w) // define window with alias w
.groupBy('w, 'a) // group the table by attribute a and window w
.select('a, 'b.sum) // aggregate
Window properties such as the start, end, or rowtime timestamp of a time window can be added in the select statement as a property of the window alias as w.start
, w.end
, and w.rowtime
, respectively. The window start and rowtime timestamps are the inclusive lower and uppper window boundaries. In contrast, the window end timestamp is the exclusive upper window boundary. For example a tumbling window of 30 minutes that starts at 2pm would have 14:00:00.000
as start timestamp, 14:29:59.999
as rowtime timestamp, and 14:30:00.000
as end timestamp.
Table table = input
.window([Window w].as("w")) // define window with alias w
.groupBy("w, a") // group the table by attribute a and window w
.select("a, w.start, w.end, w.rowtime, b.count"); // aggregate and add window start, end, and rowtime timestamps
val table = input
.window([w: Window] as 'w) // define window with alias w
.groupBy('w, 'a) // group the table by attribute a and window w
.select('a, 'w.start, 'w.end, 'w.rowtime, 'b.count) // aggregate and add window start, end, and rowtime timestamps
The Window
parameter defines how rows are mapped to windows. Window
is not an interface that users can implement. Instead, the Table API provides a set of predefined Window
classes with specific semantics, which are translated into underlying DataStream
or DataSet
operations. The supported window definitions are listed below.
A tumbling window assigns rows to non-overlapping, continuous windows of fixed length. For example, a tumbling window of 5 minutes groups rows in 5 minutes intervals. Tumbling windows can be defined on event-time, processing-time, or on a row-count.
Tumbling windows are defined by using the Tumble
class as follows:
Method | Description |
---|---|
over |
Defines the length the window, either as time or row-count interval. |
on |
The time attribute to group (time interval) or sort (row count) on. For batch queries this might be any Long or Timestamp attribute. For streaming queries this must be a declared event-time or processing-time time attribute. |
as |
Assigns an alias to the window. The alias is used to reference the window in the following groupBy() clause and optionally to select window properties such as window start, end, or rowtime timestamps in the select() clause. |
// Tumbling Event-time Window
.window(Tumble.over("10.minutes").on("rowtime").as("w"));
// Tumbling Processing-time Window (assuming a processing-time attribute "proctime")
.window(Tumble.over("10.minutes").on("proctime").as("w"));
// Tumbling Row-count Window (assuming a processing-time attribute "proctime")
.window(Tumble.over("10.rows").on("proctime").as("w"));
// Tumbling Event-time Window
.window(Tumble over 10.minutes on 'rowtime as 'w)
// Tumbling Processing-time Window (assuming a processing-time attribute "proctime")
.window(Tumble over 10.minutes on 'proctime as 'w)
// Tumbling Row-count Window (assuming a processing-time attribute "proctime")
.window(Tumble over 10.rows on 'proctime as 'w)
A sliding window has a fixed size and slides by a specified slide interval. If the slide interval is smaller than the window size, sliding windows are overlapping. Thus, rows can be assigned to multiple windows. For example, a sliding window of 15 minutes size and 5 minute slide interval assigns each row to 3 different windows of 15 minute size, which are evaluated in an interval of 5 minutes. Sliding windows can be defined on event-time, processing-time, or on a row-count.
Sliding windows are defined by using the Slide
class as follows:
Method | Description |
---|---|
over |
Defines the length of the window, either as time or row-count interval. |
every |
Defines the slide interval, either as time or row-count interval. The slide interval must be of the same type as the size interval. |
on |
The time attribute to group (time interval) or sort (row count) on. For batch queries this might be any Long or Timestamp attribute. For streaming queries this must be a declared event-time or processing-time time attribute. |
as |
Assigns an alias to the window. The alias is used to reference the window in the following groupBy() clause and optionally to select window properties such as window start, end, or rowtime timestamps in the select() clause. |
// Sliding Event-time Window
.window(Slide.over("10.minutes").every("5.minutes").on("rowtime").as("w"));
// Sliding Processing-time window (assuming a processing-time attribute "proctime")
.window(Slide.over("10.minutes").every("5.minutes").on("proctime").as("w"));
// Sliding Row-count window (assuming a processing-time attribute "proctime")
.window(Slide.over("10.rows").every("5.rows").on("proctime").as("w"));
// Sliding Event-time Window
.window(Slide over 10.minutes every 5.minutes on 'rowtime as 'w)
// Sliding Processing-time window (assuming a processing-time attribute "proctime")
.window(Slide over 10.minutes every 5.minutes on 'proctime as 'w)
// Sliding Row-count window (assuming a processing-time attribute "proctime")
.window(Slide over 10.rows every 5.rows on 'proctime as 'w)
Session windows do not have a fixed size but their bounds are defined by an interval of inactivity, i.e., a session window is closes 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 or processing-time.
A session window is defined by using the Session
class as follows:
Method | Description |
---|---|
withGap |
Defines the gap between two windows as time interval. |
on |
The time attribute to group (time interval) or sort (row count) on. For batch queries this might be any Long or Timestamp attribute. For streaming queries this must be a declared event-time or processing-time time attribute. |
as |
Assigns an alias to the window. The alias is used to reference the window in the following groupBy() clause and optionally to select window properties such as window start, end, or rowtime timestamps in the select() clause. |
// Session Event-time Window
.window(Session.withGap("10.minutes").on("rowtime").as("w"));
// Session Processing-time Window (assuming a processing-time attribute "proctime")
.window(Session.withGap("10.minutes").on("proctime").as("w"));
// Session Event-time Window
.window(Session withGap 10.minutes on 'rowtime as 'w)
// Session Processing-time Window (assuming a processing-time attribute "proctime")
.window(Session withGap 10.minutes on 'proctime as 'w)
Over window aggregates are known from standard SQL (OVER
clause) and defined in the SELECT
clause of a query. Unlike group windows, which are specified in the GROUP BY
clause, over windows do not collapse rows. Instead over window aggregates compute an aggregate for each input row over a range of its neighboring rows.
Over windows are defined using the window(w: OverWindow*)
clause and referenced via an alias in the select()
method. The following example shows how to define an over window aggregation on a table.
Table table = input
.window([OverWindow w].as("w")) // define over window with alias w
.select("a, b.sum over w, c.min over w"); // aggregate over the over window w
val table = input
.window([w: OverWindow] as 'w) // define over window with alias w
.select('a, 'b.sum over 'w, 'c.min over 'w) // aggregate over the over window w
The OverWindow
defines a range of rows over which aggregates are computed. OverWindow
is not an interface that users can implement. Instead, the Table API provides the Over
class to configure the properties of the over window. Over windows can be defined on event-time or processing-time and on ranges specified as time interval or row-count. The supported over window definitions are exposed as methods on Over
(and other classes) and are listed below:
Method | Required | Description |
---|---|---|
partitionBy |
Optional |
Defines a partitioning of the input on one or more attributes. Each partition is individually sorted and aggregate functions are applied to each partition separately. Note: In streaming environments, over window aggregates can only be computed in parallel if the window includes a partition by clause. Without |
orderBy |
Required |
Defines the order of rows within each partition and thereby the order in which the aggregate functions are applied to rows. Note: For streaming queries this must be a declared event-time or processing-time time attribute. Currently, only a single sort attribute is supported. |
preceding |
Required |
Defines the interval of rows that are included in the window and precede the current row. The interval can either be specified as time or row-count interval. Bounded over windows are specified with the size of the interval, e.g., Unbounded over windows are specified using a constant, i.e., |
following |
Optional |
Defines the window interval of rows that are included in the window and follow the current row. The interval must be specified in the same unit as the preceding interval (time or row-count). At the moment, over windows with rows following the current row are not supported. Instead you can specify one of two constants:
If the |
as |
Required |
Assigns an alias to the over window. The alias is used to reference the over window in the following |
Note: Currently, all aggregation functions in the same select()
call must be computed of the same over window.
// Unbounded Event-time over window (assuming an event-time attribute "rowtime")
.window(Over.partitionBy("a").orderBy("rowtime").preceding("unbounded_range").as("w"));
// Unbounded Processing-time over window (assuming a processing-time attribute "proctime")
.window(Over.partitionBy("a").orderBy("proctime").preceding("unbounded_range").as("w"));
// Unbounded Event-time Row-count over window (assuming an event-time attribute "rowtime")
.window(Over.partitionBy("a").orderBy("rowtime").preceding("unbounded_row").as("w"));
// Unbounded Processing-time Row-count over window (assuming a processing-time attribute "proctime")
.window(Over.partitionBy("a").orderBy("proctime").preceding("unbounded_row").as("w"));
// Unbounded Event-time over window (assuming an event-time attribute "rowtime")
.window(Over partitionBy 'a orderBy 'rowtime preceding UNBOUNDED_RANGE as 'w)
// Unbounded Processing-time over window (assuming a processing-time attribute "proctime")
.window(Over partitionBy 'a orderBy 'proctime preceding UNBOUNDED_RANGE as 'w)
// Unbounded Event-time Row-count over window (assuming an event-time attribute "rowtime")
.window(Over partitionBy 'a orderBy 'rowtime preceding UNBOUNDED_ROW as 'w)
// Unbounded Processing-time Row-count over window (assuming a processing-time attribute "proctime")
.window(Over partitionBy 'a orderBy 'proctime preceding UNBOUNDED_ROW as 'w)
// Bounded Event-time over window (assuming an event-time attribute "rowtime")
.window(Over.partitionBy("a").orderBy("rowtime").preceding("1.minutes").as("w"))
// Bounded Processing-time over window (assuming a processing-time attribute "proctime")
.window(Over.partitionBy("a").orderBy("proctime").preceding("1.minutes").as("w"))
// Bounded Event-time Row-count over window (assuming an event-time attribute "rowtime")
.window(Over.partitionBy("a").orderBy("rowtime").preceding("10.rows").as("w"))
// Bounded Processing-time Row-count over window (assuming a processing-time attribute "proctime")
.window(Over.partitionBy("a").orderBy("proctime").preceding("10.rows").as("w"))
// Bounded Event-time over window (assuming an event-time attribute "rowtime")
.window(Over partitionBy 'a orderBy 'rowtime preceding 1.minutes as 'w)
// Bounded Processing-time over window (assuming a processing-time attribute "proctime")
.window(Over partitionBy 'a orderBy 'proctime preceding 1.minutes as 'w)
// Bounded Event-time Row-count over window (assuming an event-time attribute "rowtime")
.window(Over partitionBy 'a orderBy 'rowtime preceding 10.rows as 'w)
// Bounded Processing-time Row-count over window (assuming a processing-time attribute "proctime")
.window(Over partitionBy 'a orderBy 'proctime preceding 10.rows as 'w)
The Table API is built on top of Flinkās DataSet and DataStream APIs. Internally, it also uses Flinkās TypeInformation
to define data types. Fully supported types are listed in org.apache.flink.table.api.Types
. The following table summarizes the relation between Table API types, SQL 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.SQL_DATE |
DATE |
java.sql.Date |
Types.SQL_TIME |
TIME |
java.sql.Time |
Types.SQL_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 |
Types.MULTISET |
MULTISET |
e.g. java.util.HashMap<String, Integer> for a multiset of String |
Generic types and composite types (e.g., POJOs or Tuples) can be fields of a row as well. Generic types are treated as a black box and can be passed on or processed by user-defined functions. Composite types can be accessed with built-in functions (see Value access functions section).
Some of the operators in previous sections expect one or more expressions. Expressions can be specified using an embedded Scala DSL or as Strings. Please refer to the examples above to learn how expressions can be specified.
This is the EBNF grammar for expressions:
expressionList = expression , { "," , expression } ;
expression = timeIndicator | overConstant | alias ;
alias = logic | ( logic , "as" , fieldReference ) | ( logic , "as" , "(" , fieldReference , { "," , fieldReference } , ")" ) ;
logic = comparison , [ ( "&&" | "||" ) , comparison ] ;
comparison = term , [ ( "=" | "==" | "===" | "!=" | "!==" | ">" | ">=" | "<" | "<=" ) , term ] ;
term = product , [ ( "+" | "-" ) , product ] ;
product = unary , [ ( "*" | "/" | "%") , unary ] ;
unary = [ "!" | "-" | "+" ] , composite ;
composite = over | suffixed | nullLiteral | prefixed | atom ;
suffixed = interval | suffixAs | suffixCast | suffixIf | suffixDistinct | suffixFunctionCall ;
prefixed = prefixAs | prefixCast | prefixIf | prefixDistinct | prefixFunctionCall ;
interval = timeInterval | rowInterval ;
timeInterval = composite , "." , ("year" | "years" | "month" | "months" | "day" | "days" | "hour" | "hours" | "minute" | "minutes" | "second" | "seconds" | "milli" | "millis") ;
rowInterval = composite , "." , "rows" ;
suffixCast = composite , ".cast(" , dataType , ")" ;
prefixCast = "cast(" , expression , dataType , ")" ;
dataType = "BYTE" | "SHORT" | "INT" | "LONG" | "FLOAT" | "DOUBLE" | "BOOLEAN" | "STRING" | "DECIMAL" | "SQL_DATE" | "SQL_TIME" | "SQL_TIMESTAMP" | "INTERVAL_MONTHS" | "INTERVAL_MILLIS" | ( "MAP" , "(" , dataType , "," , dataType , ")" ) | ( "PRIMITIVE_ARRAY" , "(" , dataType , ")" ) | ( "OBJECT_ARRAY" , "(" , dataType , ")" ) ;
suffixAs = composite , ".as(" , fieldReference , ")" ;
prefixAs = "as(" , expression, fieldReference , ")" ;
suffixIf = composite , ".?(" , expression , "," , expression , ")" ;
prefixIf = "?(" , expression , "," , expression , "," , expression , ")" ;
suffixDistinct = composite , "distinct.()" ;
prefixDistinct = functionIdentifier , ".distinct" , [ "(" , [ expression , { "," , expression } ] , ")" ] ;
suffixFunctionCall = composite , "." , functionIdentifier , [ "(" , [ expression , { "," , expression } ] , ")" ] ;
prefixFunctionCall = functionIdentifier , [ "(" , [ expression , { "," , expression } ] , ")" ] ;
atom = ( "(" , expression , ")" ) | literal | fieldReference ;
fieldReference = "*" | identifier ;
nullLiteral = "Null(" , dataType , ")" ;
timeIntervalUnit = "YEAR" | "YEAR_TO_MONTH" | "MONTH" | "DAY" | "DAY_TO_HOUR" | "DAY_TO_MINUTE" | "DAY_TO_SECOND" | "HOUR" | "HOUR_TO_MINUTE" | "HOUR_TO_SECOND" | "MINUTE" | "MINUTE_TO_SECOND" | "SECOND" ;
timePointUnit = "YEAR" | "MONTH" | "DAY" | "HOUR" | "MINUTE" | "SECOND" | "QUARTER" | "WEEK" | "MILLISECOND" | "MICROSECOND" ;
over = composite , "over" , fieldReference ;
overConstant = "current_row" | "current_range" | "unbounded_row" | "unbounded_row" ;
timeIndicator = fieldReference , "." , ( "proctime" | "rowtime" ) ;
Here, literal
is a valid Java literal, fieldReference
specifies a column in the data (or all columns if *
is used), and functionIdentifier
specifies a supported scalar function. The
column names and function names follow Java identifier syntax. Expressions specified as Strings can also use prefix notation instead of suffix notation to call operators and functions.
If working with exact numeric values or large decimals is required, the Table API also supports Javaās BigDecimal type. In the Scala Table API decimals can be defined by BigDecimal("123456")
and in Java by appending a āpā for precise e.g. 123456p
.
In order to work with temporal values the Table API supports Java SQLās Date, Time, and Timestamp types. In the Scala Table API literals can be defined by using java.sql.Date.valueOf("2016-06-27")
, java.sql.Time.valueOf("10:10:42")
, or java.sql.Timestamp.valueOf("2016-06-27 10:10:42.123")
. The Java and Scala Table API also support calling "2016-06-27".toDate()
, "10:10:42".toTime()
, and "2016-06-27 10:10:42.123".toTimestamp()
for converting Strings into temporal types. Note: Since Javaās temporal SQL types are time zone dependent, please make sure that the Flink Client and all TaskManagers use the same time zone.
Temporal intervals can be represented as number of months (Types.INTERVAL_MONTHS
) or number of milliseconds (Types.INTERVAL_MILLIS
). Intervals of same type can be added or subtracted (e.g. 1.hour + 10.minutes
). Intervals of milliseconds can be added to time points (e.g. "2016-08-10".toDate + 5.days
).
The Table API comes with a set of built-in functions for data transformations. This section gives a brief overview of the available functions.
Comparison functions | Description |
---|---|
|
Equals. |
|
Not equal. |
|
Greater than. |
|
Greater than or equal. |
|
Less than. |
|
Less than or equal. |
|
Returns true if the given expression is null. |
|
Returns true if the given expression is not null. |
|
Returns true, if a string matches the specified LIKE pattern. E.g. "Jo_n%" matches all strings that start with "Jo(arbitrary letter)n". |
|
Returns true, if a string matches the specified SQL regex pattern. E.g. "A+" matches all strings that consist of at least one "A". |
|
Returns true if an expression exists in a given list of expressions. This is a shorthand for multiple OR conditions. If the testing set contains null, the result will be null if the element can not be found and true if it can be found. If element is null, the result is always null. E.g. "42.in(1, 2, 3)" leads to false. |
|
Returns true if an expression exists in a given table sub-query. The sub-query table must consist of one column. This column must have the same data type as the expression. Note: For streaming queries the operation is rewritten in a join and group operation. The required state to compute the query result might grow infinitely depending on the number of distinct input rows. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
|
Returns true if the given expression is between lowerBound and upperBound (both inclusive). False otherwise. The parameters must be numeric types or identical comparable types. |
|
Returns true if the given expression is not between lowerBound and upperBound (both inclusive). False otherwise. The parameters must be numeric types or identical comparable types. |
Logical functions | Description |
---|---|
|
Returns true if boolean1 is true or boolean2 is true. Supports three-valued logic. |
|
Returns true if boolean1 and boolean2 are both true. Supports three-valued logic. |
|
Returns true if boolean expression is not true; returns null if boolean is null. |
|
Returns true if the given boolean expression is true. False otherwise (for null and false). |
|
Returns true if given boolean expression is false. False otherwise (for null and true). |
|
Returns true if the given boolean expression is not true (for null and false). False otherwise. |
|
Returns true if given boolean expression is not false (for null and true). False otherwise. |
Arithmetic functions | Description |
---|---|
|
Returns numeric. |
|
Returns negative numeric. |
|
Returns numeric1 plus numeric2. |
|
Returns numeric1 minus numeric2. |
|
Returns numeric1 multiplied by numeric2. |
|
Returns numeric1 divided by numeric2. |
|
Returns numeric1 raised to the power of numeric2. |
|
Calculates the absolute value of given value. |
|
Returns the remainder (modulus) of numeric1 divided by numeric2. The result is negative only if numeric1 is negative. |
|
Calculates the square root of a given value. |
|
Calculates the natural logarithm of given value. |
|
Calculates the base 10 logarithm of given value. |
|
Calculates the logarithm of a given numeric value. If called without a parameter, this function returns the natural logarithm of |
|
Calculates the Euler's number raised to the given power. |
|
Calculates the smallest integer greater than or equal to a given number. |
|
Calculates the largest integer less than or equal to a given number. |
|
Calculates the sine of a given number. |
|
Calculates the cosine of a given number. |
|
Calculates the tangent of a given number. |
|
Calculates the cotangent of a given number. |
|
Calculates the arc sine of a given number. |
|
Calculates the arc cosine of a given number. |
|
Calculates the arc tangent of a given number. |
|
Converts numeric from radians to degrees. |
|
Converts numeric from degrees to radians. |
|
Calculates the signum of a given number. |
|
Rounds the given number to integer places right to the decimal point. |
|
Returns a value that is closer than any other value to pi. |
|
Returns a value that is closer than any other value to e. |
|
Returns a pseudorandom double value between 0.0 (inclusive) and 1.0 (exclusive). |
|
Returns a pseudorandom double value between 0.0 (inclusive) and 1.0 (exclusive) with a initial seed. Two rand functions will return identical sequences of numbers if they have same initial seed. |
|
Returns a pseudorandom integer value between 0.0 (inclusive) and the specified value (exclusive). |
|
Returns a pseudorandom integer value between 0.0 (inclusive) and the specified value (exclusive) with a initial seed. Two randInteger functions will return identical sequences of numbers if they have same initial seed and same bound. |
|
Returns a string representation of an integer numeric value in binary format. Returns null if numeric is null. E.g. "4" leads to "100", "12" leads to "1100". |
String functions | Description |
---|---|
|
Concatenates two character strings. |
|
Returns the length of a String. |
|
Returns all of the characters in a string in upper case using the rules of the default locale. |
|
Returns all of the characters in a string in lower case using the rules of the default locale. |
|
Returns the position of string in an other string starting at 1. Returns 0 if string could not be found. E.g. |
|
Removes leading and/or trailing characters from the given string. By default, whitespaces at both sides are removed. |
|
Replaces a substring of string with a string starting at a position (starting at 1). An optional length specifies how many characters should be removed. E.g. |
|
Creates a substring of the given string beginning at the given index to the end. The start index starts at 1 and is inclusive. |
|
Creates a substring of the given string at the given index for the given length. The index starts at 1 and is inclusive, i.e., the character at the index is included in the substring. The substring has the specified length or less. |
|
Converts the initial letter of each word in a string to uppercase. Assumes a string containing only [A-Za-z0-9], everything else is treated as whitespace. |
|
Returns a string left-padded with the given pad string to a length of len characters. If the string is longer than len, the return value is shortened to len characters. E.g. "hi".lpad(4, '??') returns "??hi", "hi".lpad(1, '??') returns "h". |
|
Returns a string right-padded with the given pad string to a length of len characters. If the string is longer than len, the return value is shortened to len characters. E.g. "hi".rpad(4, '??') returns "hi??", "hi".rpad(1, '??') returns "h". |
|
Returns the string that results from concatenating the arguments. Returns NULL if any argument is NULL. E.g. |
|
Returns the string that results from concatenating the arguments using a separator. The separator is added between the strings to be concatenated. Returns NULL If the separator is NULL. concat_ws() does not skip empty strings. However, it does skip any NULL argument. E.g. |
Conditional functions | Description |
---|---|
|
Ternary conditional operator that decides which of two other expressions should be evaluated based on a evaluated boolean condition. E.g. |
Type conversion functions | Description |
---|---|
|
Converts a value to a given type. E.g. |
Value constructor functions | Description |
---|---|
|
Creates an interval of rows. |
Temporal functions | Description |
---|---|
|
Parses a date string in the form "yy-mm-dd" to a SQL date. |
|
Parses a time string in the form "hh:mm:ss" to a SQL time. |
|
Parses a timestamp string in the form "yy-mm-dd hh:mm:ss.fff" to a SQL timestamp. |
|
Creates an interval of months for a given number of years. |
|
Creates an interval of months for a given number of months. |
|
Creates an interval of milliseconds for a given number of days. |
|
Creates an interval of milliseconds for a given number of hours. |
|
Creates an interval of milliseconds for a given number of minutes. |
|
Creates an interval of milliseconds for a given number of seconds. |
|
Creates an interval of milliseconds. |
|
Returns the current SQL date in UTC time zone. |
|
Returns the current SQL time in UTC time zone. |
|
Returns the current SQL timestamp in UTC time zone. |
|
Returns the current SQL time in local time zone. |
|
Returns the current SQL timestamp in local time zone. |
|
Extracts parts of a time point or time interval. Returns the part as a long value. E.g. |
|
Rounds a time point down to the given unit. E.g. |
|
Rounds a time point up to the given unit. E.g. |
|
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 |
|
Attention This function has serious bugs and should not be used for now. Please implement a custom UDF instead or use extract() as a workaround. |
Aggregate functions | Description |
---|---|
|
Returns the number of input rows for which the field is not null. |
|
Returns the average (arithmetic mean) of the numeric field across all input values. |
|
Returns the sum of the numeric field across all input values. If all values are null, null is returned. |
|
Returns the sum of the numeric field across all input values. If all values are null, 0 is returned. |
|
Returns the maximum value of field across all input values. |
|
Returns the minimum value of field across all input values. |
|
Returns the population standard deviation of the numeric field across all input values. |
|
Returns the sample standard deviation of the numeric field across all input values. |
|
Returns the population variance (square of the population standard deviation) of the numeric field across all input values. |
|
Returns the sample variance (square of the sample standard deviation) of the numeric field across all input values. |
|
Returns the multiset aggregate of the input value. |
Value access functions | Description |
---|---|
|
Accesses the field of a Flink composite type (such as Tuple, POJO, etc.) by index or name and returns it's value. E.g. |
|
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. In most cases the fields of the flat representation are named similarly to the original fields but with a dollar separator (e.g. |
Array functions | Description |
---|---|
|
Creates an array from a list of values. The array will be an array of objects (not primitives). |
|
Returns the number of elements of an array. |
|
Returns the element at a particular position in an array. The index starts at 1. |
|
Returns the sole element of an array with a single element. Returns |
Map functions | Description |
---|---|
|
Creates a map from a list of key-value pairs. |
|
Returns the number of entries of a map. |
|
Returns the value specified by a particular key in a map. |
Hash functions | Description |
---|---|
|
Returns the MD5 hash of the string argument as a string of 32 hexadecimal digits; null if string is null. |
|
Returns the SHA-1 hash of the string argument as a string of 40 hexadecimal digits; null if string is null. |
|
Returns the SHA-224 hash of the string argument as a string of 56 hexadecimal digits; null if string is null. |
|
Returns the SHA-256 hash of the string argument as a string of 64 hexadecimal digits; null if string is null. |
|
Returns the SHA-384 hash of the string argument as a string of 96 hexadecimal digits; null if string is null. |
|
Returns the SHA-512 hash of the string argument as a string of 128 hexadecimal digits; null if string is null. |
|
Returns the hash using the SHA-2 family of hash functions (SHA-224, SHA-256, SHA-384, or SHA-512). The first argument string is the string to be hashed. hashLength is the bit length of the result (either 224, 256, 384, or 512). Returns null if string or hashLength is null. |
Row functions | Description |
---|---|
|
Creates a row from a list of values. Row is composite type and can be access via value access functions. |
Auxiliary functions | Description |
---|---|
|
Specifies a name for an expression i.e. a field. Additional names can be specified if the expression expands to multiple fields. |
Comparison functions | Description |
---|---|
|
Equals. |
|
Not equal. |
|
Greater than. |
|
Greater than or equal. |
|
Less than. |
|
Less than or equal. |
|
Returns true if the given expression is null. |
|
Returns true if the given expression is not null. |
|
Returns true, if a string matches the specified LIKE pattern. E.g. "Jo_n%" matches all strings that start with "Jo(arbitrary letter)n". |
|
Returns true, if a string matches the specified SQL regex pattern. E.g. "A+" matches all strings that consist of at least one "A". |
|
Returns true if an expression exists in a given list of expressions. This is a shorthand for multiple OR conditions. If the testing set contains null, the result will be null if the element can not be found and true if it can be found. If element is null, the result is always null. E.g. "42".in(1, 2, 3) leads to false. |
|
Returns true if an expression exists in a given table sub-query. The sub-query table must consist of one column. This column must have the same data type as the expression. Note: This operation is not supported in a streaming environment yet. Note: For streaming queries the operation is rewritten in a join and group operation. The required state to compute the query result might grow infinitely depending on the number of distinct input rows. Please provide a query configuration with valid retention interval to prevent excessive state size. See Streaming Concepts for details. |
|
Returns true if the given expression is between lowerBound and upperBound (both inclusive). False otherwise. The parameters must be numeric types or identical comparable types. |
|
Returns true if the given expression is not between lowerBound and upperBound (both inclusive). False otherwise. The parameters must be numeric types or identical comparable types. |
Logical functions | Description |
---|---|
|
Returns true if boolean1 is true or boolean2 is true. Supports three-valued logic. |
|
Returns true if boolean1 and boolean2 are both true. Supports three-valued logic. |
|
Returns true if boolean expression is not true; returns null if boolean is null. |
|
Returns true if the given boolean expression is true. False otherwise (for null and false). |
|
Returns true if given boolean expression is false. False otherwise (for null and true). |
|
Returns true if the given boolean expression is not true (for null and false). False otherwise. |
|
Returns true if given boolean expression is not false (for null and true). False otherwise. |
Arithmetic functions | Description |
---|---|
|
Returns numeric. |
|
Returns negative numeric. |
|
Returns numeric1 plus numeric2. |
|
Returns numeric1 minus numeric2. |
|
Returns numeric1 multiplied by numeric2. |
|
Returns numeric1 divided by numeric2. |
|
Returns numeric1 raised to the power of numeric2. |
|
Calculates the absolute value of given value. |
|
Returns the remainder (modulus) of numeric1 divided by numeric2. The result is negative only if numeric1 is negative. |
|
Calculates the square root of a given value. |
|
Calculates the natural logarithm of given value. |
|
Calculates the base 10 logarithm of given value. |
|
Calculates the logarithm of a given numeric value. If called without a parameter, this function returns the natural logarithm of |
|
Calculates the Euler's number raised to the given power. |
|
Calculates the smallest integer greater than or equal to a given number. |
|
Calculates the largest integer less than or equal to a given number. |
|
Calculates the sine of a given number. |
|
Calculates the cosine of a given number. |
|
Calculates the cotangent of a given number. |
|
Calculates the arc sine of a given number. |
|
Calculates the arc cosine of a given number. |
|
Calculates the arc tangent of a given number. |
|
Calculates the tangent of a given number. |
|
Converts numeric from radians to degrees. |
|
Converts numeric from degrees to radians. |
|
Calculates the signum of a given number. |
|
Rounds the given number to integer places right to the decimal point. |
|
Returns a value that is closer than any other value to pi. |
|
Returns a value that is closer than any other value to e. |
|
Returns a pseudorandom double value between 0.0 (inclusive) and 1.0 (exclusive). |
|
Returns a pseudorandom double value between 0.0 (inclusive) and 1.0 (exclusive) with a initial seed. Two rand functions will return identical sequences of numbers if they have same initial seed. |
|
Returns a pseudorandom integer value between 0.0 (inclusive) and the specified value (exclusive). |
|
Returns a pseudorandom integer value between 0.0 (inclusive) and the specified value (exclusive) with a initial seed. Two randInteger functions will return identical sequences of numbers if they have same initial seed and same bound. |
|
Returns a string representation of an integer numeric value in binary format. Returns null if numeric is null. E.g. "4" leads to "100", "12" leads to "1100". |
Arithmetic functions | Description |
---|---|
|
Concatenates two character strings. |
|
Returns the length of a String. |
|
Returns all of the characters in a string in upper case using the rules of the default locale. |
|
Returns all of the characters in a string in lower case using the rules of the default locale. |
|
Returns the position of string in an other string starting at 1. Returns 0 if string could not be found. E.g. |
|
Removes leading and/or trailing characters from the given string. |
|
Replaces a substring of string with a string starting at a position (starting at 1). An optional length specifies how many characters should be removed. E.g. |
|
Creates a substring of the given string beginning at the given index to the end. The start index starts at 1 and is inclusive. |
|
Creates a substring of the given string at the given index for the given length. The index starts at 1 and is inclusive, i.e., the character at the index is included in the substring. The substring has the specified length or less. |
|
Converts the initial letter of each word in a string to uppercase. Assumes a string containing only [A-Za-z0-9], everything else is treated as whitespace. |
Conditional functions | Description |
---|---|
|
Ternary conditional operator that decides which of two other expressions should be evaluated based on a evaluated boolean condition. E.g. |
Type conversion functions | Description |
---|---|
|
Converts a value to a given type. E.g. |
Value constructor functions | Description |
---|---|
|
Creates an interval of rows. |
Temporal functions | Description |
---|---|
|
Parses a date string in the form "yy-mm-dd" to a SQL date. |
|
Parses a time string in the form "hh:mm:ss" to a SQL time. |
|
Parses a timestamp string in the form "yy-mm-dd hh:mm:ss.fff" to a SQL timestamp. |
|
Creates an interval of months for a given number of years. |
|
Creates an interval of months for a given number of months. |
|
Creates an interval of milliseconds for a given number of days. |
|
Creates an interval of milliseconds for a given number of hours. |
|
Creates an interval of milliseconds for a given number of minutes. |
|
Creates an interval of milliseconds for a given number of seconds. |
|
Creates an interval of milliseconds. |
|
Returns the current SQL date in UTC time zone. |
|
Returns the current SQL time in UTC time zone. |
|
Returns the current SQL timestamp in UTC time zone. |
|
Returns the current SQL time in local time zone. |
|
Returns the current SQL timestamp in local time zone. |
|
Extracts parts of a time point or time interval. Returns the part as a long value. E.g. |
|
Rounds a time point down to the given unit. E.g. |
|
Rounds a time point up to the given unit. E.g. |
|
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 |
Aggregate functions | Description |
---|---|
|
Returns the number of input rows for which the field is not null. |
|
Returns the average (arithmetic mean) of the numeric field across all input values. |
|
Returns the sum of the numeric field across all input values. If all values are null, null is returned. |
|
Returns the sum of the numeric field across all input values. If all values are null, 0 is returned. |
|
Returns the maximum value of field across all input values. |
|
Returns the minimum value of field across all input values. |
|
Returns the population standard deviation of the numeric field across all input values. |
|
Returns the sample standard deviation of the numeric field across all input values. |
|
Returns the population variance (square of the population standard deviation) of the numeric field across all input values. |
|
Returns the sample variance (square of the sample standard deviation) of the numeric field across all input values. |
|
Returns the multiset aggregate of the input value. |
Value access functions | Description |
---|---|
|
Accesses the field of a Flink composite type (such as Tuple, POJO, etc.) by index or name and returns it's value. E.g. |
|
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. In most cases the fields of the flat representation are named similarly to the original fields but with a dollar separator (e.g. |
|
Attention This function has serious bugs and should not be used for now. Please implement a custom UDF instead or use extract() as a workaround. |
Array functions | Description |
---|---|
|
Creates an array from a list of values. The array will be an array of objects (not primitives). |
|
Returns the number of elements of an array. |
|
Returns the element at a particular position in an array. The index starts at 1. |
|
Returns the sole element of an array with a single element. Returns |
Map functions | Description |
---|---|
|
Creates a map from a list of key-value pairs. |
|
Returns the number of entries of a map. |
|
Returns the value specified by a particular key in a map. |
Hash functions | Description |
---|---|
|
Returns the MD5 hash of the string argument as a string of 32 hexadecimal digits; null if string is null. |
|
Returns the SHA-1 hash of the string argument as a string of 40 hexadecimal digits; null if string is null. |
|
Returns the SHA-224 hash of the string argument as a string of 56 hexadecimal digits; null if string is null. |
|
Returns the SHA-256 hash of the string argument as a string of 64 hexadecimal digits; null if string is null. |
|
Returns the SHA-384 hash of the string argument as a string of 96 hexadecimal digits; null if string is null. |
|
Returns the SHA-512 hash of the string argument as a string of 128 hexadecimal digits; null if string is null. |
|
Returns the hash using the SHA-2 family of hash functions (SHA-224, SHA-256, SHA-384, or SHA-512). The first argument string is the string to be hashed. hashLength is the bit length of the result (either 224, 256, 384, or 512). Returns null if string or hashLength is null. |
Row functions | Description |
---|---|
|
Creates a row from a list of values. Row is composite type and can be access via value access functions. |
Auxiliary functions | Description |
---|---|
|
Specifies a name for an expression i.e. a field. Additional names can be specified if the expression expands to multiple fields. |
The following operations are not supported yet: