Thanks Mohammed, it’s good to know I’m not alone!
How easy is it to integrate Zeppelin with Spark on Cassandra? It looks like it would only support Hadoop out of the box. Is it just a case of dropping the Cassandra Connector onto the Spark classpath? Cheers, Matthew *From:* Mohammed Guller [mailto:moham...@glassbeam.com] *Sent:* 20 June 2015 17:27 *To:* shahid ashraf *Cc:* Matthew Johnson; user@spark.apache.org *Subject:* RE: Code review - Spark SQL command-line client for Cassandra It is a simple Play-based web application. It exposes an URI for submitting a SQL query. It then executes that query using CassandraSQLContext provided by Spark Cassandra Connector. Since it is web-based, I added an authentication and authorization layer to make sure that only users with the right authorization can use it. I am happy to open-source that code if there is interest. Just need to carve out some time to clean it up and remove all the other services that this web application provides. Mohammed *From:* shahid ashraf [mailto:sha...@trialx.com <sha...@trialx.com>] *Sent:* Saturday, June 20, 2015 6:52 AM *To:* Mohammed Guller *Cc:* Matthew Johnson; user@spark.apache.org *Subject:* RE: Code review - Spark SQL command-line client for Cassandra Hi Mohammad Can you provide more info about the Service u developed On Jun 20, 2015 7:59 AM, "Mohammed Guller" <moham...@glassbeam.com> wrote: Hi Matthew, It looks fine to me. I have built a similar service that allows a user to submit a query from a browser and returns the result in JSON format. Another alternative is to leave a Spark shell or one of the notebooks (Spark Notebook, Zeppelin, etc.) session open and run queries from there. This model works only if people give you the queries to execute. Mohammed *From:* Matthew Johnson [mailto:matt.john...@algomi.com] *Sent:* Friday, June 19, 2015 2:20 AM *To:* user@spark.apache.org *Subject:* Code review - Spark SQL command-line client for Cassandra Hi all, I have been struggling with Cassandra’s lack of adhoc query support (I know this is an anti-pattern of Cassandra, but sometimes management come over and ask me to run stuff and it’s impossible to explain that it will take me a while when it would take about 10 seconds in MySQL) so I have put together the following code snippet that bundles DataStax’s Cassandra Spark connector and allows you to submit Spark SQL to it, outputting the results in a text file. Does anyone spot any obvious flaws in this plan?? (I have a lot more error handling etc in my code, but removed it here for brevity) *private* *void* run(String sqlQuery) { SparkContext scc = *new* SparkContext(conf); CassandraSQLContext csql = *new* CassandraSQLContext(scc); DataFrame sql = csql.sql(sqlQuery); String folderName = "/tmp/output_" + System.*currentTimeMillis*(); *LOG*.info("Attempting to save SQL results in folder: " + folderName); sql.rdd().saveAsTextFile(folderName); *LOG*.info("SQL results saved"); } *public* *static* *void* main(String[] args) { String sparkMasterUrl = args[0]; String sparkHost = args[1]; String sqlQuery = args[2]; SparkConf conf = *new* SparkConf(); conf.setAppName("Java Spark SQL"); conf.setMaster(sparkMasterUrl); conf.set("spark.cassandra.connection.host", sparkHost); JavaSparkSQL app = *new* JavaSparkSQL(conf); app.run(sqlQuery, printToConsole); } I can then submit this to Spark with ‘spark-submit’: Ø *./spark-submit --class com.algomi.spark.JavaSparkSQL --master spark://sales3:7077 spark-on-cassandra-0.0.1-SNAPSHOT-jar-with-dependencies.jar spark://sales3:7077 sales3 "select * from mykeyspace.operationlog" * It seems to work pretty well, so I’m pretty happy, but wondering why this isn’t common practice (at least I haven’t been able to find much about it on Google) – is there something terrible that I’m missing? Thanks! Matthew
