Artem Krylysov

How RocksDB works

Introduction #

Over the past years, the adoption of RocksDB increased dramatically. It became a standard for embeddable key-value stores.

Today RocksDB runs in production at Meta, Microsoft, Netflix, Uber. At Meta RocksDB serves as a storage engine for the MySQL deployment powering the distributed graph database.

Big tech companies are not the only RocksDB users. Several startups were built around RocksDB - CockroachDB, Yugabyte, PingCAP, Rockset.

I spent the past 4 years at Datadog building and running services on top of RocksDB in production. In this post, I'll give a high-level overview of how RocksDB works.

Let's build a Full-Text Search engine

Full-Text Search is one of those tools people use every day without realizing it. If you ever googled "golang coverage report" or tried to find "indoor wireless camera" on an e-commerce website, you used some kind of full-text search.

Full-Text Search (FTS) is a technique for searching text in a collection of documents. A document can refer to a web page, a newspaper article, an email message, or any structured text.

Today we are going to build our own FTS engine. By the end of this post, we'll be able to search across millions of documents in less than a millisecond. We'll start with simple search queries like "give me all documents that contain the word cat" and we'll extend the engine to support more sophisticated boolean queries.

String interning in Go

String interning is a technique of storing only one copy of each unique string in memory. It can significantly reduce memory usage for applications that store many duplicated strings.

Handling C++ exceptions in Go

Cgo is a mechanism that allows Go packages call C code. The Go compiler enables cgo for every .go source file that imports a special pseudo package "C". The text in the comment before the import "C" line is treated as a C code. You can include headers, define functions, types and variables - everything a normal C code can do:

package main

#include <stdio.h>

void foo(int x) {
    printf("x: %d\n", x);
import "C"

func main() { // x: 123

Profiling and optimizing Go web applications


This post was updated on 2021-04-25.

Go has a powerful built-in profiler that supports CPU, memory, goroutine and block (contention) profiling.

Enabling the profiler #

Go provides a low-level profiling API runtime/pprof, but if you are developing a long-running service, it's more convenient to work with a high-level net/http/pprof package.

All you need to enable the profiler is to import net/http/pprof and it will automatically register the required HTTP handlers:

package main

import (
    _ "net/http/pprof"

func hiHandler(w http.ResponseWriter, r *http.Request) {

func main() {
    http.HandleFunc("/", hiHandler)
    http.ListenAndServe(":8080", nil)

Benchmark of Python JSON libraries


This post was updated on 2016-08-13: added python-rapidjson; updated simplejson and ujson.

A couple of weeks ago after spending some time with Python profiler, I discovered that Python’s json module is not as fast as I expected. I decided to benchmark alternative JSON libraries.

Производительность С++ STL regex

Столкнулся недавно с простой задачей - нужно было найти позицию открывающегося тега <body> в HTML странице. Не долго думая я решил использовать регулярные выражения, через минуту у меня родился регексп <body[^>]*>. Все работало хорошо, пока дело не дошло до тестирования на больших объемах данных.

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