Diving Into Spark’s Cost-Based Optimizer

Ron Hu, et al, explain how Spark’s cost-based optimizer works:

At its core, Spark’s Catalyst optimizer is a general library for representing query plans as trees and sequentially applying a number of optimization rules to manipulate them. A majority of these optimization rules are based on heuristics, i.e., they only account for a query’s structure and ignore the properties of the data being processed, which severely limits their applicability. Let us demonstrate this with a simple example. Consider a query shown below that filters a table t1 of size 500GB and joins the output with another table t2of size 20GB. Spark implements this query using a hash join by choosing the smaller join relation as the build side (to build a hash table) and the larger relation as the probe side 1. Given that t2 is smaller than t1, Apache Spark 2.1 would choose the right side as the build side without factoring in the effect of the filter operator (which in this case filters out the majority of t1‘s records). Choosing the incorrect side as the build side often forces the system to give up on a fast hash join and turn to sort-merge join due to memory constraints.

Click through for a very interesting look at this query optimzier.

Related Posts

HDFS Federation

Sangeeta Gulia explains what HDFS Federation is and how it differs from classic HDFS: HDFS Federation improves the existing HDFS architecture through a clear separation of namespace and storage, enabling generic block storage layer. It enables support for multiple namespaces in the cluster to improve scalability and isolation. Federation also opens up the architecture, expanding […]

Read More

An Apache Sqoop Tutorial

Subham Sinha has an introductory-level tutorial on Apache Sqoop: For Hadoop developer, the actual game starts after the data is being loaded in HDFS. They play around this data in order to gain various insights hidden in the data stored in HDFS. So, for this analysis the data residing in the relational database management systems […]

Read More

Categories

September 2017
MTWTFSS
« Aug Oct »
 123
45678910
11121314151617
18192021222324
252627282930