Summary

In this chapter, we covered the use of the RethinkDB query language to perform data exploration queries. Apart from that, we also looked over some use cases where we need to perform some alteration and filtering of records in order to meet our exploration task, such as stripping the $ sign from ctc, or converting base 256 ip addresses into base 10 values and performing a query on them. We also covered some general uses cases in order to get a practical feel of ReQL.

In the next chapter, we are going to study performance tuning in RethinkDB. As we have mentioned in Chapter 1, The RethinkDB Architecture and Data Model, RethinkDB comes up with an easy-to-use administrative screen to perform sharding, replication, and so on. We will also look over clustering and running queries in a cluster. Then we will cover query optimization in RethinkDB and tools that can help us to identify query execution time, waiting time, and so on.