Re: Spark Structured Streaming 'bool' object is not callable, quitting

yes indeed Russell, a silly mistake by me. Thanks view my Linkedin profile *Disclaimer:* Use it at your own risk. Any and all responsibility for any loss, damage or destruction of data or any other property which may arise from

Re: Spark Structured Streaming 'bool' object is not callable, quitting

Apologies it was a mistake by me. The correct syntax is without additional () *print(streamingDummy.isStreaming)* It returns True Thanks view my Linkedin profile *Disclaimer:* Use it at your own risk. Any and all

Re: Spark Structured Streaming 'bool' object is not callable, quitting

Callable means you tried to treat a field as a function like in the following example >>> fun = True >>> fun() Traceback (most recent call last): File "", line 1, in TypeError: 'bool' object is not callable My guess is that "isStreaming" is a bool, and in your syntax you used it as a function

Spark Structured Streaming 'bool' object is not callable, quitting

Hi, I am testing something in Spark Structured Streaming, this is a new topic Typical kafka json row dummy2 = StructType().add("uuid", StringType()).add("timecreated", TimestampType()).add("status", StringType()) # example ##856095c6-cdec-485b-9da6-d78275bc0a25

Benchmarks for Many-to-Many Joins

Hi I wanted to ask if anyone knows any datasets or benchmarks which I can use for evaluating many-to-many joins (as depicted in the attached snapshot). I looked at TPC-H and TPC-DS benchmarks but surprisingly, they mostly have one-to-many

Graceful shutdown SPARK Structured Streaming

Dear friends, is there any documentation available for gracefully stopping SPARK Structured Streaming in 3.1.x? I am referring to articles which are 4 to 5 years old and was wondering whether there is a better way available today to gracefully shutdown a SPARK streaming job. Thanks a ton in

Re: Loading Hadoop-Azure in Kubernetes

Okay! It is a good approach too, I'm happy that you got it working. Cheers, Pol Santamaria On Tue, Apr 20, 2021 at 10:23 AM Nisd wrote: > I ended up with this solution: > https://stackoverflow.com/a/67173899/1020941 > > > > -- > Sent from: http://apache-spark-user-list.1001560.n3.nabble.com/