This document provides an overview of Google Bigtable, a distributed storage system for structured data. It discusses Bigtable's design including its use of column families, row keys, and versioning. It also describes Bigtable's basic implementation including its use of the Google File System (GFS) and how data is divided into tablets and distributed across tablet servers. The document then discusses related systems like HBase and how it compares to Bigtable. It provides examples of Bigtable's performance and real-world usage at Google. Finally, it poses some thoughts for discussion and provides useful references for further information.

1. Google Bigtable (Bigtable: A Distributed Storage System for Structured Data) Komadinovic Vanja, Vast Platform team

5. Design

7. Design

8. Basic implementation

10. GFS - HDFS introduction: overview

12. MapReduce introduction: overview

14. Implementation: overview

15. Implementation: oragnization - two special tables: ROOT and METADATA - ROOT never gets splitted - location of ROOT is in Chubby file - estimated ROOT size 128Mb => 2^34 tablets - METADATA contains all user tablets, row key is an encoding of the tablet’s table identifier and its end row

17. HBase - Apache Bigtable solution

20. Performance and usage case - number of 1000-byte values read/written per second - table shows the rate per tablet server Experiment 1 TS 50 TS 250 TS 500 TS random reads 1212 593 479 241 random reads mem 10811 8511 8000 6250 random writes 8850 3745 3425 2000 sequential reads 4425 2463 2625 2469 sequential writes 8547 3623 2451 1905 scans 15385 10526 9524 7843

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