Some Good Papers in SIGMOD 2018

In this post, I write my reading report for papers in SIGMOD 2018. I will go through all the papers that I am interested and write their basic ideas, methods and my personal evaluations. Since this is definitely a long process, this post will be updated frequently. Also, please let me know if you find anything inappropriate.

Written on June 15, 2018

How to Integrate Your Stuff into Spark SQL

Spark SQL is a module in Apache Spark that enables relational processing (e.g., declarative queries) using Spark’s functional programming API. Spark SQL also provides a declarative DataFrame API to bridge between relational and procedural processing. It supports both external data sources (e.g., JSON, Parquet and Avro) and internal data collections (i.e., RDDs). Besides, it uses a highly extensible optimizer Catalyst, making it easy to add complex rules, control code generation, and define extension points.

Written on November 7, 2017

System Overview: LevelDB

LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. Many of its ideas and techniques are widely used in Big Data stacks, e.g., BigTable and HBase. The code in LevelDB is well-written with good documents, which is a ideal project to learn from.

Written on March 17, 2017

In the Code: User-Defined Function(UDF) in Spark SQL

This post illustrates the implementations of UDF in Spark SQL, where the targeted version is Spark 1.6.0 and the targeted language is Scala. I will talk about UDF in roughly two parts: registration and execution.

Written on December 2, 2016

Bulk Loading in HBase with Practice in MR & Spark

Bulk loading is a feature of HBase for ingesting tons of data efficiently. In this post, I are going to share some basic concepts of bulk loading and its practice in MapReduce and Spark.

Written on May 15, 2016