HeartSaVioR commented on a change in pull request #27268: [SPARK-30553][DOCS]
fix structured-streaming java example error
URL: https://github.com/apache/spark/pull/27268#discussion_r368290007
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File path: docs/structured-streaming-programming-guide.md
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@@ -978,11 +978,11 @@ val windowedCounts = words
Dataset<Row> words = ... // streaming DataFrame of schema { timestamp:
Timestamp, word: String }
// Group the data by window and word and compute the count of each group
-Dataset<Row> windowedCounts = words
- .withWatermark("timestamp", "10 minutes")
+Dataset<Row> wordsWatermark = words.withWatermark("timestamp", "10 minutes");
+Dataset<Row> windowedCounts = wordsWatermark
.groupBy(
- functions.window(words.col("timestamp"), "10 minutes", "5 minutes"),
- words.col("word"))
+ functions.window(wordsWatermark.col("timestamp"), "10 minutes", "5
minutes"),
Review comment:
I guess `functions.col("timestamp")` is exactly equivalent to the
`$"timestamp"` in Scala code example. Same applies to col("word").
Actually Java code example seems to be written a bit verbosely. `import
static org.apache.spark.sql.functions.*;` would shorten the code and remove
`functions.` all the places - actually Scala code example assume that the
import is placed before.
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