viirya commented on a change in pull request #33691:
URL: https://github.com/apache/spark/pull/33691#discussion_r687063401
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File path: docs/structured-streaming-programming-guide.md
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@@ -1134,6 +1134,73 @@ sessionizedCounts = events \
</div>
</div>
+Instead of static value, we can also provide an expression to specify gap
duration dynamically
+based on the input row. Note that the rows with negative or zero gap duration
will be filtered
+out from the aggregation.
+
+<div class="codetabs">
+<div data-lang="scala" markdown="1">
+
+{% highlight scala %}
+import spark.implicits._
+
+val events = ... // streaming DataFrame of schema { timestamp: Timestamp,
userId: String }
+
+val sessionWindow = SessionWindow($"timestamp".expr, when($"userId" ===
"user1", "5 seconds")
+ .when($"userId" === "user2", "20 seconds")
+ .otherwise("5 minutes")
+
+// Group the data by session window and userId, and compute the count of each
group
+val sessionizedCounts = events
+ .withWatermark("timestamp", "10 minutes")
+ .groupBy(
+ Column(sessionWindow),
+ $"userId")
+ .count()
+{% endhighlight %}
+
+</div>
+<div data-lang="java" markdown="1">
+
+{% highlight java %}
+Dataset<Row> events = ... // streaming DataFrame of schema { timestamp:
Timestamp, userId: String }
+
+SessionWindow sessionWindow = new SessionWindow(col("timestamp").expr,
when(col("userId").equalTo("user1"), "5 seconds")
+ .when(col("userId").equalTo("user2"), "20 seconds")
+ .otherwise("5 minutes"))
+
+// Group the data by session window and userId, and compute the count of each
group
+Dataset<Row> sessionizedCounts = events
+ .withWatermark("timestamp", "10 minutes")
+ .groupBy(
+ new Column(sessionWindow),
+ col("userId"))
+ .count();
+{% endhighlight %}
+
+</div>
+<div data-lang="python" markdown="1">
+{% highlight python %}
+from pyspark.sql import functions as F
+
+events = ... # streaming DataFrame of schema { timestamp: Timestamp, userId:
String }
+
+session_window = session_window(events.timestamp, \
Review comment:
Oh, I don't realize python `session_window` doesn't accept an
expression...
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