Random sampling from hash files

Random Sampling from Database Files: A Survey

In this paper we survey known results on algorithms, data structures, and some applications of random sampling from databases. We first discuss various reasons for sampling from databases, and for inclusion of sampling as a DBMS operator. We consider basic sampling algorithms, sampling from trees, sampling from hash tables, and auxiliary memory resident index information to facilitate sampling.

Testing Forensic Hash Tools on Sparse Files

Forensic hash tools are usually used to prove and protect the integrity of digital evidence: When a file is intercepted by law enforcement, a cryprographic fingerprint is taken by using a forensic hash tool. If later in a court of law the identical fingerprint can be computed from the presented evidence, the evidence is taken to be original. In this paper we demonstrate that most of the freely ...

Random Sampling from Databases

Random Sampling from Databases by Frank Olken Doctor of Philosophy in Computer Science University of California at Berkeley Professor Michael Stonebraker, Chair In this thesis I describe e cient methods of answering random sampling queries of relational databases, i.e., retrieving random samples of the results of relational queries. I begin with a discussion of the motivation for including samp...

Random Sampling from Boltzmann Principles

Random Sampling from B+ Trees

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...