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====== Window

Tumble Window

Tumbling windows are consecutive, non-overlapping windows of a specified fixed length. For example, a tumbling window of 5 minutes size groups elements in 5 minutes intervals.

Example: ::

>>> from pyflink.table.expressions import col, lit
>>> Tumble.over(lit(10).minutes) \
...       .on(col("rowtime")) \
...       .alias("w")

.. currentmodule:: pyflink.table.window

.. autosummary:: :toctree: api/

Tumble.over
TumbleWithSize.on
TumbleWithSizeOnTime.alias

Sliding Window

Sliding windows have a fixed size and slide by a specified slide interval. If the slide interval is smaller than the window size, sliding windows are overlapping. Thus, an element can be assigned to multiple windows.

For example, a sliding window of size 15 minutes with 5 minutes sliding interval groups elements of 15 minutes and evaluates every five minutes. Each element is contained in three consecutive window evaluations.

Example: ::

>>> from pyflink.table.expressions import col, lit
>>> Slide.over(lit(10).minutes) \
...      .every(lit(5).minutes) \
...      .on(col("rowtime")) \
...      .alias("w")

.. currentmodule:: pyflink.table.window

.. autosummary:: :toctree: api/

Slide.over
SlideWithSize.every
SlideWithSizeAndSlide.on
SlideWithSizeAndSlideOnTime.alias

Session Window

The boundary of session windows are defined by intervals of inactivity, i.e., a session window is closes if no event appears for a defined gap period.

Example: ::

>>> from pyflink.table.expressions import col, lit
>>> Session.with_gap(lit(10).minutes) \\
...        .on(col("rowtime")) \\
...        .alias("w")

.. currentmodule:: pyflink.table.window

.. autosummary:: :toctree: api/

Session.with_gap
SessionWithGap.on
SessionWithGapOnTime.alias

Over Window

Similar to SQL, over window aggregates compute an aggregate for each input row over a range of its neighboring rows.

Example: ::

>>> from pyflink.table.expressions import col, UNBOUNDED_RANGE
>>> Over.partition_by(col("a")) \
...     .order_by(col("rowtime")) \
...     .preceding(UNBOUNDED_RANGE) \
...     .alias("w")

.. currentmodule:: pyflink.table.window

.. autosummary:: :toctree: api/

Over.order_by
Over.partition_by
OverWindowPartitionedOrdered.alias
OverWindowPartitionedOrdered.preceding
OverWindowPartitionedOrderedPreceding.alias
OverWindowPartitionedOrderedPreceding.following
OverWindowPartitioned.order_by