1989•Very Large Data BasesRequires access

Random sampling from B + trees

Frank Olken, Doron Rotem

Open publisher page 65 citations

Abstract

We consider the design and analysis of algorithms to retrieve simple random samples from databases. Specifically, we examine simple random sampling from B+ tree files. Existing methods of sampling from B+ trees, require the use of auxiliary rank information in the nodes of the tree. Such modified B+ tree files are called “ranked B+ trees”. We compare sampling from ranked Bt tree files, with new acceptance/rejection (A/R) sampling methods which sample directly from standard B+ trees. Our new A/R sampling algorithm can easily be retrofit to existing DBMSs, and does not require the overhead of maintaining rank information. We consider both iterative and batch sampling methods.

About this research paper

What this paper is about

We consider the design and analysis of algorithms to retrieve simple random samples from databases. Specifically, we examine simple random sampling from B+ tree files. Existing methods of sampling from B+ trees, require the use of auxiliary rank information in the nodes of the tree. Such modified B+ tree files are called “ranked B+ trees”. We compare sampling from ranked Bt tree files, with new acceptance/rejection (A/R) sampling methods which sample directly from standard B+ trees. Our new A/R sampling algorithm can easily be retrofit to existing DBMSs, and does not require the overhead of maintaining rank information. We consider both iterative and batch sampling methods.

Why it matters

OpenAlex reports 65 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

We consider the design and analysis of algorithms to retrieve simple random samples from databases. Specifically, we examine simple random sampling from B+ tree files. Existing methods of sampling from B+ trees, require the use of auxiliary rank information in the nodes of the tree. Such modified B+ tree files are called “ranked B+ trees”. We compare sampling from ranked Bt tree files, with new acceptance/rejection (A/R) sampling methods which sample directly from standard B+ trees. Our new A/R sampling algorithm can easily be retrofit to existing DBMSs, and does not require the overhead of maintaining rank information. We consider both iterative and batch sampling methods.

Key concepts: Simple random sample, Sampling (signal processing), Computer science, Tree (set theory), Systematic sampling, Sampling design, B-tree, Slice sampling

Related papers

Back to paper searchBrowse research topicsOriginal source
Random sampling from B + trees — Research Paper | ScholarLens