Section 1 # 1

1. CS 7651. The AgeofInfinite Storage Section 1 # 1

2. 1. The AgeofInfinite Storagehas begun Many of us have enough money in our pockets right now to buy all the storage we will be able to fill for the next 5 years. So having the storage capacity is no longer a problem. Managing it is a problem (especially when the volume gets large). How much data is there? Section 1 # 2

3. Googi 10100 . . . Yotta 1024 Zetta 1021 Exa 1018 Peta 1015 Tera 1012 Giga 109 Mega 106 Kilo 103 • Tera Bytes (TBs) are Here • 1 TB costs < 1k$ to buy • 1 TB may cost ~ 300k$/year to own • Management and curation are the expensive part • Searching 1 TB takes hours • I’m Terrified byTeraBytes • I’m Petrified by PetaBytes We are here • I’m completely Exafied by ExaBytes • I’m too old to ever be Zettafied by ZettaBytes, but you may be in your lifetime. • You may be Yottafied by YottaBytes. • You may not be Googified byGoogiBytes, but the next generation may be? Section 1 # 3

4. Yotta Zetta Exa Peta Tera Giga Mega Kilo Section 1 # 4 How much information is there? Everything! Recorded • Soon everything can be recorded and indexed. • Most of it will never be seen by humans. • Data summarization, trend detection, anomaly detection, data mining, are key technologies All Books MultiMedia All books (words) .Movie A Photo A Book 10-24 Yocto, 10-21 zepto, 10-18 atto, 10-15 femto, 10-12 pico, 10-9 nano, 10-6 micro, 10-3 milli

5. First Disk, in 1956 • IBM 305 RAMAC • 4 MB • 50 24” disks • 1200 rpm (revolutions per minute) • 100 milli-seconds (ms) access time • 35k$/year to rent • Included computer & accounting software(tubes not transistors) 7th Grade C.S. lab Tech. Section 1 # 5

6. 10 years later 30 MB 1.6 meters Section 1 # 6

7. Kilo Mega Giga Tera Peta Exa Zetta Yotta Disk Evolution Section 1 # 8

8. MemexAs We May Think, Vannevar Bush, 1945 “A memex is a device in which an individual stores all his books, records, and communications, and which is mechanized so that it may be consulted with exceeding speed and flexibility” “yet if the user inserted 5000 pages of material a day it would take him hundreds of years to fill the repository, so that he can enter material freely” Section 1 # 9

9. Can you fill a terabyte in a year? Section 1 # 10

10. On a Personal Terabyte,How Will We Find Anything? • Need Queries, Indexing, Data Mining, Scalability, Replication… • If you don’t use a DBMS, you will implement one of your own! • Need for Data Mining, Machine Learning is more important then ever! Of the digital data in existence today, • 80% is personal/individual • 20% is Corporate/Governmental DBMS Section 1 # 11

11. I made up these Name! Projected data sizes are overrunning our ability to name their orders of magnitude! We’re awash with data! • Network data: • 100 terabytes ~ 1014 Bytes • US EROS Data Center archives Earth Observing System (near Sioux Falls SD) Remotely Sensed satellite and aerial imagery data • 15 petabytes ~ 1016 Bytes • National Virtual Observatory (aggregated astronomical data) • 10 exabytes ~ 1019 Bytes • Sensor data from sensors (including Micro & Nano -sensor networks) • 10 zettabytes ~ 1022 Bytes • WWW (and other text collections) • 10 yottabytes by 2020 ~ 1025 Bytes • Genomic/Proteomic/Metabolomic data (microarrays, genechips, genome sequences) • 10 gazillabytes by 2030 ~ 1028 Bytes? • Stock Market prediction data (prices + all the above?) • 10 supragazillabytes by 2040 ~ 1031 Bytes? Useful information must be teased out of these large volumes of raw data. AND these are some of the 1/5th of Corporate or Governmental data collections. The other 4/5ths of data sets are personnel! Section 1 # 12

12. Parkinson’s Law(for data) • Data expands to fill available storage • Disk-storage version of Moore’s Law • Available storage doubles every 9 months! • How do we get the information we need from the massive volumes of data we will have? • Querying (for the information we know is there) • Data mining (for answers to questions we don't know to ask precisely • Moore’s Law with respect to processor performance seems to be over (processor performance doubles every x months…). Note that the processors we find in our computers today are the same (or less powerful) as the ones we found a few years ago. That’s because that technology seems to have reached a limit (minaturizing). Now the directions is to put multiple processor on the same chip or die (e.g. Itel Nehalem has 16 or more) and to use other types of processor (such as General Purpose Graphics Processor, GP-GPUs) to increase performance. Main memory sizes are shooting up. What does that mean for database systems? Section 3 # 13

13. Section 3 # 1 Thank you.