datastax-enterprise

One of our nodes in our 3 node cluster is down and on checking the log file, it shows the below messages INFO [keyspace.core Index WorkPool work thread-2] 2016-09-14 14:05:32,891 AbstractMetrics.java:114 - Cannot record QUEUE latency of 11 minutes because higher than 10 minutes. INFO [keyspace.core Index WorkPool work thread-2] 2016-09-14 14:05:33,233 AbstractMetrics.java:114 - Cannot record QUEUE latency of 10 minutes because higher than 10 minutes. WARN [keyspace.core Index WorkPool work thread-2] 2016-09-14 14:05:33,398 Worker.java:99 - Interrupt/timeout detected. java.util.concurrent

I am planning to try Solr's docValues to hopefully improve facet and sort performance. I have some questions around this feature: If I enable docValues, will Solr create a forward index (for faceting) in addition to a separate reverse index (for searching)? Or will Solr simply create a forward index ONLY? (thus, resulting to performance gain in faceting in exchange for performance loss in searching) If I want to both facet and search in a single field, what is the best practice? Should I set "indexed=true" and "docValues=true" in the same field or should I create a copy field where the source

Requirement is simple: we have to create a table which will have only 24 hours of data. We have two options Defile TTL with each insert Make table property default_time_to_live for 24 hours. I have general idea about both the things but internally which one will be helpful to deal with tombstones? or both will generate same amount of tombstones? Which one will be better and why any reference link will be appreciated. If a table has default_time_to_live on it then rows that exceed this time limit are deleted immediately without tombstones being written. This will not affect rows / columns that

I'm using Datastax Enterprise 4.8.3. I'm trying to implement a Quartz based application to remotely submit Spark jobs. During my research I have stumbled upon the following links: Apache Spark Hidden REST API Spark feature - Provide a stable application submission gateway in standalone cluster mode To test out the theory I tried executing the below code snippet on the master node (IP: "spark-master-ip"; directly on the shell) of my 2 node cluster (as provided in link #1 above): curl -X POST http://spark-master-ip:6066/v1/submissions/create --header "Content-Type:application/json;charset=UTF-8"

I'm running Datastax Enterprise in a cluster consisting of 3 nodes. They are all running under the same hardware: 2 Core Intel Xeon 2.2 Ghz, 7 GB RAM, 4 TB Raid-0 This should be enough for running a cluster with a light load, storing less than 1 GB of data. Most of the time, everything is just fine but it appears that sometimes the running tasks related to the Repair Service in OpsCenter sometimes get stuck; this causes an instability in that node and an increase in load. However, if the node is restarted, the stuck tasks don't show up and the load is at normal levels again. Because of the

I have an old Cassandra cluster that needs to be brought back into life. I would like to clear out all the user and system data, all stored tokens, everything and start from a clean slate - is there a recommended way of doing this? Here's the procedure I use for Apache Cassandra: First stop Cassandra on all the nodes, then on each node: rm -r <the commitlog_directory specified in cassandra.yaml> rm -r <the data_file_directories specified in cassandra.yaml> rm <the contents of the saved_caches_directory specified in cassandra.yaml> rm <old logfiles in /var/log/cassandra/> Then restart the