Thanks @George Vetticaden! As @Jonas Straub and @Andrew Grande mentioned, in this example I used cloud mode (notice that Solr was started with -c -z arguments) but you can easily change the Solr processor to point to Solr standalone instance too ... View more

In case it helps, we had been able to access data from Phoenix as Spark RDD using early version of HDP 2.3 (Spark 1.3). See steps here ... View more

Thanks @Alex Miller this was exactly the issue we were debugging today ... View more

I'm surprised it wasn't @bbende@hortonworks.com who wrote this article 😉 ... View more

Zeppelin Ambari service has been updated to install the updated TP Zeppelin bits for Spark 1.4.1 and 1.3.1. The update will be made for 1.5.1 this week after the TP is out Also the Magellan notebook has also been updated with documentation and to enable it to run standalone on 1.4.1 ... View more

Installed this through the Ambari service for testing and basic Spark, SparkSQL, PySpark seem ok Couple of issues: 1. tried out the Magellan blog notebook (after modifying it to include the %dep from the blog) and the UberRecord cell errors out: From the log: 5/10/24 10:48:06 INFO SchedulerFactory: Job remoteInterpretJob_1445708886505 started by scheduler org.apache.zeppelin.spark.SparkInterpreter313266037 15/10/24 10:48:06 ERROR Job: Job failed scala.reflect.internal.Types$TypeError: bad symbolic reference. A signature in Shape.class refers to term geometry in value com.core which is not available. It may be completely missing from the current classpath, or the version on the classpath might be incompatible with the version used when compiling Shape.class. at scala.reflect.internal.pickling.UnPickler$Scan.toTypeError(UnPickler.scala:847) at scala.reflect.internal.pickling.UnPickler$Scan$LazyTypeRef.complete(UnPickler.scala:854) at scala.reflect.internal.pickling.UnPickler$Scan$LazyTypeRef.load(UnPickler.scala:863) at scala.reflect.internal.Symbols$Symbol.typeParams(Symbols.scala:1489) at scala.tools.nsc.transform.SpecializeTypes$$anonfun$scala$tools$nsc$transform$SpecializeTypes$$normalizeMember$1.apply(SpecializeTypes.scala:798) at scala.tools.nsc.transform.SpecializeTypes$$anonfun$scala$tools$nsc$transform$SpecializeTypes$$normalizeMember$1.apply(SpecializeTypes.scala:798) at scala.reflect.internal.SymbolTable.atPhase(SymbolTable.scala:207) at scala.reflect.internal.SymbolTable.beforePhase(SymbolTable.scala:215) at scala.tools.nsc.transform.SpecializeTypes.scala$tools$nsc$transform$SpecializeTypes$$norma (side note: this notebook doesn't seem to have much documentation on what its doing like the other...would be good to add) 2. The blog currently says the below This technical preview can be installed on any HDP 2.3.x cluster ...however 2.3.0 comes with Spark 1.3.1 which will not work unless they manually install Spark 1.4.1 TP so either: a) we may want to include steps for those users too (esp since the current version of the sandbox comes with 1.3.1) b) explicitly ask users to try the Zeppelin TP with 2.3.2 ... View more

What OS are you running on? ... View more