This tutorial provides the big-picture view the documentation lacks. Though you will get your hands on many of ES's features, we won't waste your time slogging page by page through the reference manual—you can look up specific corner cases any time. Instead, we will give you the mental framework to organize—and even predict—the specifics. Without assuming you know anything about Lucene, we will pull back the curtain to explore the data structures used for indexing, the algorithms that make faceting so fast, and the tradeoffs involved in replication and sharding. From these fundamentals, you will be able to deduce how to make your own use cases efficient. You will also see how far ES can be stretched, applying some clever Python preprocessing to do things like trigram-accelerated regex matching. Finally, you will learn to avoid the mistakes we made, both in design and deployment, so you can build a stable cluster that needs no babysitting.