Pros:
No need for Scala skills, Java can be used.
Other companies are already doing it.
> Support Yarn execution
But not only…
Complex use-case for import can easily be done in Java (see
https://spark-summit.org/eu-2017/events/extending-apache-sparks-ingestion-building-your-own-java-data-source/
Or Databaricks Delta (announced at Spark Summit) or IBM Event Store depending
on the use case.
On Oct 31, 2017, at 14:30, Joseph Pride
mailto:jos...@versanalytics.com>> wrote:
Folks:
SnappyData.
I’m fairly new to working with it myself, but it looks pretty promising. It
marries Spark with a
Hello, I'm trying to run the following code,
var newContextCreated = false // Flag to detect whether new context
was created or not
val kafkaBrokers = "localhost:9092" // comma separated list of broker:host
private val batchDuration: Duration = Seconds(3)
private val master: String = "local[2]"
p
Hi Daniel,
Several things:
1) Your error seems to suggest you're using a different version of Spark
and a different version of the sql-kafka connector. Could you make sure
they are on the same Spark version?
2) With Structured Streaming, you may remove everything related to a
StreamingContext.
Hello Experts,
I am required to use a specific user id to save files on a remote hdfs
cluster. Remote in the sense, spark jobs run on EMR and write to a CDH
cluster. Hence I cannot change the hdfs-site.xml etc to point to the
destination cluster. As a result I am using webhdfs to save the files in
Sorry Michael, I ended up using kafka and missed noticing your message.
Yes, I did specify the schema with read.schema and thats when I got:
at
org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$.org$apache$spark$sql$catalyst$analysis$UnsupportedOperationChecker$$throwError(Unsupp