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Diffstat (limited to 'docs/structured-streaming-programming-guide.md')
| -rw-r--r-- | docs/structured-streaming-programming-guide.md | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/docs/structured-streaming-programming-guide.md b/docs/structured-streaming-programming-guide.md index 995ac77a4f..7988472378 100644 --- a/docs/structured-streaming-programming-guide.md +++ b/docs/structured-streaming-programming-guide.md @@ -539,7 +539,7 @@ spark = SparkSession. ... # Read text from socket socketDF = spark \ - .readStream() \ + .readStream \ .format("socket") \ .option("host", "localhost") \ .option("port", 9999) \ @@ -552,7 +552,7 @@ socketDF.printSchema() # Read all the csv files written atomically in a directory userSchema = StructType().add("name", "string").add("age", "integer") csvDF = spark \ - .readStream() \ + .readStream \ .option("sep", ";") \ .schema(userSchema) \ .csv("/path/to/directory") # Equivalent to format("csv").load("/path/to/directory") @@ -971,7 +971,7 @@ Here is the compatibility matrix. <br/><br/> Update mode uses watermark to drop old aggregation state. <br/><br/> - Complete mode does drop not old aggregation state since by definition this mode + Complete mode does not drop old aggregation state since by definition this mode preserves all data in the Result Table. </td> </tr> @@ -1201,13 +1201,13 @@ noAggDF = deviceDataDf.select("device").where("signal > 10") # Print new data to console noAggDF \ - .writeStream() \ + .writeStream \ .format("console") \ .start() # Write new data to Parquet files noAggDF \ - .writeStream() \ + .writeStream \ .format("parquet") \ .option("checkpointLocation", "path/to/checkpoint/dir") \ .option("path", "path/to/destination/dir") \ @@ -1218,14 +1218,14 @@ aggDF = df.groupBy("device").count() # Print updated aggregations to console aggDF \ - .writeStream() \ + .writeStream \ .outputMode("complete") \ .format("console") \ .start() # Have all the aggregates in an in memory table. The query name will be the table name aggDF \ - .writeStream() \ + .writeStream \ .queryName("aggregates") \ .outputMode("complete") \ .format("memory") \ @@ -1313,7 +1313,7 @@ query.lastProgress(); // the most recent progress update of this streaming qu <div data-lang="python" markdown="1"> {% highlight python %} -query = df.writeStream().format("console").start() # get the query object +query = df.writeStream.format("console").start() # get the query object query.id() # get the unique identifier of the running query that persists across restarts from checkpoint data @@ -1658,7 +1658,7 @@ aggDF {% highlight python %} aggDF \ - .writeStream() \ + .writeStream \ .outputMode("complete") \ .option("checkpointLocation", "path/to/HDFS/dir") \ .format("memory") \ |