kstirman
El Carro: a new open-source Kubernetes operator for Oracle from Google
Java Vector Enhancements for Apache Arrow 0.8.0 -
The technical debt you’re overlooking: Big Data Debt
I think scaling any system takes careful planning.
IMHO, this is an area where MongoDB has improved a lot in the past two years, especially with 3.0, but there is still a lot of work to do.
You can also run Hadoop MapReduce over data in MongoDB directly (24 - 29): http://www.slideshare.net/spf13/mongodb-and-hadoop
serverStatus.workingSet.pagesInMemory
pagesInMemory contains a count of the total number of pages accessed by mongod over the period displayed in overSeconds. The default page size is 4 kilobytes: to convert this value to the amount of data in memory multiply this value by 4 kilobytes.
If your total working set is less than the size of physical memory, over time the value of pagesInMemory will reflect your data size. Conversely, if your data set is greater than the size of the physical RAM, this number will reflect the total size of physical RAM.
Use pagesInMemory in conjunction with overSeconds to help estimate the actual size of the working set.
Also, there's a discussion of working set in this guide starting on page 9: http://info.10gen.com/rs/10gen/images/10gen-MongoDB_Operatio...