Github user lw-lin commented on a diff in the pull request:
https://github.com/apache/spark/pull/16442#discussion_r94271332
--- Diff: docs/structured-streaming-programming-guide.md ---
@@ -537,21 +537,21 @@ Most of the common operations on DataFrame/Dataset
are supported for streaming.
<div data-lang="scala" markdown="1">
{% highlight scala %}
-case class DeviceData(device: String, type: String, signal: Double, time:
DateTime)
+case class DeviceData(device: String, deviceType: String, signal: Double,
time: DateTime)
-val df: DataFrame = ... // streaming DataFrame with IOT device data with
schema { device: string, type: string, signal: double, time: string }
+val df: DataFrame = ... // streaming DataFrame with IOT device data with
schema { device: string, deviceType: string, signal: double, time: string }
val ds: Dataset[DeviceData] = df.as[DeviceData] // streaming Dataset
with IOT device data
// Select the devices which have signal more than 10
df.select("device").where("signal > 10") // using untyped APIs
ds.filter(_.signal > 10).map(_.device) // using typed APIs
// Running count of the number of updates for each device type
-df.groupBy("type").count() // using untyped API
+df.groupBy("deviceType").count() // using untyped
API
// Running average signal for each device type
-import org.apache.spark.sql.expressions.scalalang.typed._
-ds.groupByKey(_.type).agg(typed.avg(_.signal)) // using typed API
+import org.apache.spark.sql.expressions.scalalang.typed
+ds.groupByKey(_.deviceType).agg(typed.avg(_.signal)) // using typed API
--- End diff --
this import should be `â¦.scalalang.typed` rather than
`â¦.scalalang.typed._`
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