`windowSize` has not impact on used segments: it is only used to compute
the window end timestamp when you fetch a window, because the end-time
is not stored explicitly (as all windows are assumed to have the same
window size; i.e., it's a storage optimization to safe the bytes for
window end
Hi,
I understood how window stores are implemented using rocksdb.
When creating an instance of RocksDBWindowStore we pass two additional
arguments:
retainDuplicates
windowSize
I have not clearly understood the purpose of these two.
Like say in my application I just create one windowed store of a
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If you want to put a record into multiple window, you can do a `put()`
for each window.
The DSL uses the store in the exact same manner for hopping window
(compare the code I shared in the last reply). Even if windows are
overlapping, the
Hi,
Yes I get that when I am using the apis provided by kstream I can basically
use both:
- Tumbling time window (non-overlapping, gap-less windows)
- Hopping time window (Time-based Fixed-size, overlapping windows)
I wanted to know if I am using state store directly when created using a
What you call "sliding window" is called "hopping window" in Kafka Streams.
And yes, you can use a windowed-store for this case: In fact, a
non-overlapping tumbling window is just a special case of a hopping
window with advance == window-size.
In Kafka Streams we have a single implementation for
Hi,
So far how I have understood is that when we create a rocksdb window store;
we specify a window size and retention period.
So windows are created from epoch time based on size, say size if 100 then
windows are:
[0, 100), [100, 200), [200, 300) ...
Windows are retained based on retention
