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Firebase Presentation

on September 20, 2016

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Posting the slides from my presentation about Firebase to the Haystack Group here!

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tldr: Raft + Implementation Tips

Part of the tldr series, which summarizes papers I'm currently reading. Inspired by the morning paper.
Raft (Extended Version) + Implementation Tips [2014]Ongaro et al.

Note: For implementation tips, see the end of this blog post. Introduction Consensus algorithms The replicated state machine approach is useful for providing fault-tolerance in distributed systems. It lets a cluster of unreliable machines continue operating even when some of its members fail. In this approach, machinesusually use a replicated log to stay in sync. As shown in the figure below, each server's log stores the same commands in the same order. Every state machine executes commands from its own log in order. State machines are deterministic, so each produces the same order of outputs. Once the majority of machines have responded, the command is done executing.
Consensus algorithms ensure that the replicated log stays consistent. In the figure above, clients send commands to a server's consensus modul…

tldr: MapReduce + A Major Step Backwards?

Part of the tldr series, which summarizes papers I'm currently reading. Inspired by the morning paper.
MapReduce: Simplified Data Processing on Large Clusters (2004)Dean et al.

MapReduce is a functional programming pattern, popularized by Google for big data processing. It abstracts away parallelization, fault-tolerance, and load balancing, which allows programmers to run jobs on a distributed system through a simple but powerful 2 core API.
Programming ModelThe MapReduce library consists of two functions:
Map. (k1, v1) --> list(k2, v2). A user-defined function that takes in a key-value pair and outputs a list of intermediate key-value pairs. Reduce. (k2, list(v2)) --> list(v2). A user-defined function that takes in an intermediate key and a list of its corresponding values. It merges those values into a possibly smaller list of values. The process from beginning to end is: User specifies a list of input key-value pairs. Map takes each input key-value pair and outputs a list …

Building A Toy Language Interpreter in Go

In this post, I'll be giving a high-level overview of interpreters, why they're interesting, and how they work. I'll be referencing my repo, go_interpreter, which is a simple interpreter written in Go for a toy language. The figure below shows the structure of our interpreter with an example input:
What is an interpreter? An interpreter is a language processor that seems to directly execute the source program on user input:
In contrast, a compiler first takes in a source program and translates it to an executable machine code target program. Then, the user can pass in inputs to this target program and get outputs.
In general, an interpreter is better at reporting errors since it's processing statements one at a time, and a compiler is faster at generating outputs from inputs.

In this post, we're going to go over a simple interpreter that is capable of supporting:
integers, booleans, strings, arrays, hashmapsprefix, infix operatorsindex operatorsconditionalsglobal a…

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