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| A '''bitmap index''' is a special kind of [[Index (database)|database index]] that uses [[Bit array|bitmap]]s.
| | The Fujifilm Instax mini 8 can be a basic compact digital video camera which will take fast photos and increases them as an old style Polaroid camera. The analogue video camera seems like a stuffed toy and and is also sure to have major hipster attraction.<br><br>When we finally reside in a community the location where the prefers of Hipstamatic and Instragram reigns supreme, the Instax micro 8 is a bit more pleasurable way to get that vintage snapshot appearance.<br><br>Obtainable in 5 various colors (bright white, yellow, blue colored and pink black colored), the Instax mini 8 appears like a large boys and girls gadget by reviewing the matte plastic material complete, chunky camera lens and big control buttons. Regardless of its hulking measurement in comparison to today’s stream-lined camcorders, the Instax smaller 8 weighs about just 307g as well as being 10% leaner than past Instax styles. 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It becomes an analogue digital camera in each way.<br><br>Primarily this really is a digicam with simple principles; to help you to capture images while using ideal degree of lumination. There is 5 diverse direct exposure amounts to pick from; Inside the house, Night-time (F12.7), Gloomy, Hue (F16), Warm, Somewhat gloomy (F22), Sun-drenched and brilliant (F32). Additionall, there’s a completely new Great Essential option to capture photos with serious degrees of brightness and also a gentler atmosphere.<br><br>There is no there's and autofocus a taking pictures choice of .6m to 2.7m, so you should get up close. The flash includes a reuse period of .2-6 seconds and there exists a repaired shutter speed of 1/one minute.<br><br>The Instax smaller 8 just uses Fuji Instax motion picture which comes in packs of 10 and measure 62 by 46mm. That is about the magnitude of a credit card, so these snap shots take the tiny measurement. Packages can cost approximately £15 doing the smaller 8 a high priced purchase eventually.<br><br>To use pictures you just demand twist the dial towards the appropriate publicity amount, peer from the viewfinder and take your picture. It's as easy as that. Images can take a moment to completely produce and effects might be merged.<br><br>There is no space for fault and if you achieve it bad, being exposed concentrations and colours look away. Worst of all, you’ve thrown away among those high-priced films.<br><br>Lacking autofocus truly helps it be challenging to nail the images first time. Visuals are impressively thorough and produce the soft colour results to produce that old, Polaroid-design and style appearance, when you get it proper. 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Shapes and colours look far too rinsed out and impression lucidity is just not good, while the usually-on flash can help replace with reduced-lit up situations.<br><br>Needless to say, photographs are saved to the small area, but you do possess the big bright border at the base which means you can sign or depart a note allow it that pleasant individual impression.<br><br>Should you prefer a break through the megapixels along with the luxurious of having the ability to vacant trash pictures towards a reuse container, the Fujifilm Instax mini 8 cameras quite a bit of pleasurable. Should you are able to complement the correct direct exposure quantities together with the proper setting, it's very simple to use, and you will record some good quality images.<br><br>It provides its apparent limitations. It runs on battery power along with the movies work out very pricey after you take into account the quantity of pictures you are likely to screw up. Whenever you can admit that it is planning to amount to eventually and like the idea of owning something is not really information about adding pics to Myspace, the Instax small 8 digital camera is a amazing, classic-fashioned high-end camera that lovers of Polaroids fujifilm instax mini 8 amazon ([http://www.fujifilminstaxmini8.info/ her explanation]) will cherish.<br><br>It may possibly also develop a entertaining, basic way to introduce children to pictures.<br><br>Verdict<br><br>The Fujifilm Instax mini 8 is really an quick digicam that’s user-friendly and its a memo in the days or weeks well before digicams. The motion picture is pricey, but if you want to change the clock again, this can be a terrific retro snapper to accomplish it with. |
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| Bitmap indexes have traditionally been considered to work well for ''low-cardinality columns'', which have a modest number of distinct values, either absolutely, or relative to the number of records that contain the data. The extreme case of low cardinality is Boolean data (e.g.,Does a resident in a city have internet access?), which has two values, True and False. Bitmap indexes use [[bit array]]s (commonly called bitmaps) and answer queries by performing [[bitwise operation|bitwise logical operation]]s on these bitmaps. Bitmap indexes have a significant space and performance advantage over other structures for query of such data. Their drawback is they are less efficient than the traditional [[B-tree]] indexes for columns whose data is frequently updated: consequently, they are more often employed in read-only systems that are specialized for fast query - e.g., data warehouses, and generally unsuitable for [[online transaction processing]] applications. However, this drawback appears to apply only to their implementation in [[relational database]] management systems: certain non-relational DBMSs, notably [[InterSystems Caché|Intersystems Cache]], a hierarchical database, use bitmap indexes for [[Cardinality (SQL statements)|low-cardinality]] columns in transactional systems.
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| Some researchers argue that Bitmap indexes are also useful for moderate or even high-cardinality data (e.g., unique-valued data) which is accessed in a read-only manner, and queries access multiple bitmap-indexed columns using the AND, OR or XOR operators extensively.<ref name="sharma">[http://www.oracle.com/technetwork/articles/sharma-indexes-093638.html Bitmap Index vs. B-tree Index: Which and When?], Vivek Sharma, Oracle Technical Network.</ref>
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| Bitmap indexes are also useful in [[data warehousing]] applications for joining a large [[fact table]] to smaller [[dimension table]]s<ref>[http://www.dwoptimize.com/2007/06/101010-answer-to-life-universe-and.html ]{{dead link|date=June 2012}}</ref> such as those arranged in a [[star schema]].
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| ==Example==
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| Continuing the internet access example, a bitmap index may be logically viewed as follows:
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| {| class="wikitable" style="text-align:center; float:left"
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| |-
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| !rowspan=2| Identifier
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| !rowspan=2| HasInternet
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| !colspan=2| Bitmaps
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| |-
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| !Y !! N
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| |-
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| |1 || Yes || 1|| 0
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| |-
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| |2 || No || 0 || 1
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| |-
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| |3 || No || 0 || 1
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| |-
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| |4 || Unspecified || 0 || 0
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| |-
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| |5 || Yes || 1 || 0
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| |}
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| On the left, [[Identifier]] refers to the unique number assigned to each resident, HasInternet is the data to be indexed, the content of the bitmap index is shown as two columns under the heading ''bitmaps''. Each column in the left illustration is a ''bitmap'' in the bitmap index. In this case, there are two such bitmaps, one for "has internet" ''Yes'' and one for "has internet" ''No''. It is easy to see that each bit in bitmap ''Y'' shows whether a particular row refers to a person who has internet access. This is the simplest form of bitmap index. Most columns will have more distinct values. For example, the sales amount is likely to have a much larger number of distinct values. Variations on the bitmap index can effectively index this data as well. We briefly review three such variations.
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| Note: many of the references cited here are reviewed at.<ref>{{cite web |author=John Wu |year=2007 |title=Annotated References on Bitmap Index |url=http://www.cs.umn.edu/~kewu/annotated.html }}</ref> For those who might be interested in experimenting with some of the ideas mentioned here, many of them are implemented in open source software such as FastBit,<ref>[http://codeforge.lbl.gov/projects/fastbit/ FastBit]</ref> the Lemur Bitmap Index C++ Library,<ref>[http://code.google.com/p/lemurbitmapindex/ Lemur Bitmap Index C++ Library]</ref> the [[Apache Hive]] Data Warehouse system and [[LucidDB]].
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| {{-}}
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| ==Compression==
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| Software can [[data compression|compress]] each bitmap in a bitmap index to save space. There has been considerable amount of work on this subject.<ref>{{cite book |author=T. Johnson | editor = Malcolm P. Atkinson, Maria E. Orlowska, Patrick Valduriez, Stanley B. Zdonik, Michael L. Brodie | title = VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7–10, 1999, Edinburgh, Scotland, UK | publisher = Morgan Kaufmann | year = 1999 | isbn = 1-55860-615-7 | chapter =Performance Measurements of Compressed Bitmap Indices | pages=278–89 | url=http://www.vldb.org/conf/1999/P29.pdf }}</ref><ref>{{cite web |author=Wu K, Otoo E, Shoshani A | title=On the performance of bitmap indices for high cardinality attributes | date=March 5, 2004 | url=http://www.osti.gov/energycitations/servlets/purl/822860-LOzkmz/native/822860.pdf }}</ref>
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| Bitmap compression algorithms typically employ [[run-length encoding]], such as the Byte-aligned Bitmap Code,<ref>{{US Patent|5363098|Byte aligned data compression}}</ref> the Word-Aligned Hybrid code,<ref>{{US Patent|6831575|Word aligned bitmap compression method, data structure, and apparatus}}</ref> the Partitioned Word-Aligned Hybrid (PWAH) compression,<ref>{{cite conference |url=http://dl.acm.org/citation.cfm?doid=1989323.1989419 |title=A memory efficient reachability data structure through bit vector compression | last1=van Schaik | first1=Sebastiaan |last2=de Moor |first2=Oege |year=2011 |publisher=ACM |booktitle=Proceedings of the 2011 international conference on Management of data |pages=913–924 |location=Athens, Greece |doi=10.1145/1989323.1989419 |conference=SIGMOD '11 |isbn=978-1-4503-0661-4 }}</ref> the Position List Word Aligned Hybrid,<ref name="doi_10.1145/1739041.1739071">{{cite book | chapter = Position list word aligned hybrid: optimizing space and performance for compressed bitmaps | author = Deliège F, Pedersen TB | editor = Ioana Manolescu, Stefano Spaccapietra, Jens Teubner, Masaru Kitsuregawa, Alain Leger, Felix Naumann, Anastasia Ailamaki, and Fatma Ozcan | title = EDBT '10, Proceedings of the 13th International Conference on Extending Database Technology | publisher = ACM | location = New York, NY, USA | year = 2010 | pages = 228–39 | isbn = 978-1-60558-945-9 | doi = 10.1145/1739041.1739071 | url = http://alpha.uhasselt.be/icdt/edbticdt2010proc/edbt/papers/p0228-Deliege.pdf }}</ref> the Compressed Adaptive Index (COMPAX),<ref name="autogenerated1382">{{cite journal|author=F. Fusco, M. Stoecklin, M. Vlachos |title=NET-FLi: on-the-fly compression, archiving and indexing of streaming network traffic |date=September 2010 | volume = 3 | issue = 1–2 | pages = 1382–93 | journal=Proc. VLDB Endow | url=http://www.comp.nus.edu.sg/~vldb2010/proceedings/files/papers/I01.pdf }}</ref> Enhanced Word-Aligned Hybrid (EWAH) <ref name=ewah>{{Cite doi|10.1016/j.datak.2009.08.006}}</ref> and the COmpressed 'N' Composable Integer SEt.<ref>[http://ricerca.mat.uniroma3.it/users/colanton/concise.html Concise: Compressed 'n' Composable Integer Set]</ref><ref name="doi_10.1016/j.ipl.2010.05.018" /> These compression methods require very little effort to compress and decompress. More importantly, bitmaps compressed with BBC, WAH, COMPAX, PLWAH, EWAH and CONCISE can directly participate in [[bitwise operation]]s without decompression. This gives them considerable advantages over generic compression techniques such as [[LZ77]]. BBC compression and its derivatives are used in a commercial [[database management system]]. BBC is effective in both reducing index sizes and maintaining [[database query|query]] performance. BBC encodes the bitmaps in [[bytes]], while WAH encodes in words, better matching current [[CPU]]s. "On both synthetic data and real application data, the new word aligned schemes use only 50% more space, but perform logical operations on compressed data 12 times faster than BBC."<ref>{{cite book | author = Wu K, Otoo EJ, Shoshani A | editor = Henrique Paques, Ling Liu, and David Grossman | chapter =A Performance comparison of bitmap indexes | year=2001 | title = CIKM '01 Proceedings of the tenth international conference on Information and knowledge management | publisher = ACM | location = New York, NY, USA | pages = 559–61 | isbn = 1-58113-436-3 | doi = 10.1145/502585.502689 | url = http://crd.lbl.gov/~kewu/ps/LBNL-48975.pdf }}</ref> PLWAH bitmaps were reported to take 50% of the storage space consumed by WAH bitmaps and offer up to 20% faster performance on [[logical operation]]s.<ref name="doi_10.1145/1739041.1739071" /> Similar considerations can be done for CONCISE <ref name="doi_10.1016/j.ipl.2010.05.018">{{cite journal |author=Colantonio A, Di Pietro R | title=Concise: Compressed 'n' Composable Integer Set | journal = Information Processing Letters | volume = 110 | issue = 16 | date = 31 July 2010 | doi = 10.1016/j.ipl.2010.05.018 | url = http://ricerca.mat.uniroma3.it/users/colanton/docs/concise.pdf |pages=644–50 }}</ref> and Enhanced Word-Aligned Hybrid.<ref name="ewah"/>
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| The performance of schemes such as BBC, WAH, PLWAH, EWAH, COMPAX and CONCISE is dependent on the order of the rows. A simple lexicographical sort can divide the index size by 9 and make indexes several times faster.<ref>{{cite journal|author=D. Lemire, O. Kaser, K. Aouiche |title=Sorting improves word-aligned bitmap indexes |journal=Data & Knowledge Engineering | volume=69 | issue=1 |date=January 2010 |arxiv=0901.3751 | doi = 10.1016/j.datak.2009.08.006|pages=3–28 }}</ref> The larger the table, the more important it is to sort the rows. Reshuffling techniques have also been proposed to achieve the same results of sorting when indexing streaming data.<ref name="autogenerated1382"/>
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| ==Encoding==
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| Basic bitmap indexes use one bitmap for each distinct value. It is possible to reduce the number of bitmaps used by using a different encoding method.<ref name="autogenerated355">{{cite book |chapter=Bitmap index design and evaluation | author=C.-Y. Chan and Y. E. Ioannidis | year=1998 | title = Proceedings of the 1998 ACM SIGMOD international conference on Management of data (SIGMOD '98) | editor = Ashutosh Tiwary, Michael Franklin | publisher = ACM | location = New York, NY, USA | pages = 355–6 | doi=10.1145/276304.276336 | url = http://www.comp.nus.edu.sg/~chancy/sigmod98.pdf }}</ref><ref>{{cite book |chapter=An efficient bitmap encoding scheme for selection queries | author=C.-Y. Chan and Y. E. Ioannidis | year=1999 | title = Proceedings of the 1999 ACM SIGMOD international conference on Management of data (SIGMOD '99) | publisher = ACM | location = New York, NY, USA | pages = 215–26 | doi = 10.1145/304182.304201 | url = http://www.ist.temple.edu/~vucetic/cis616spring2005/papers/P4%20p215-chan.pdf }}</ref> For example, it is possible to encode C distinct values using log(C) bitmaps with binary encoding.<ref>{{cite journal |author = P. E. O'Neil and D. Quass| chapter = Improved Query Performance with Variant Indexes | title = Proceedings of the 1997 ACM SIGMOD international conference on Management of data (SIGMOD '97) | year = 1997 | editor = Joan M. Peckman, Sudha Ram, Michael Franklin | publisher = ACM | location = New York, NY, USA | pages = 38–49| doi=10.1145/253260.253268 }}</ref>
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| This reduces the number of bitmaps, further saving space, but to answer any query, most of the bitmaps have to be accessed. This makes it potentially not as effective as scanning a vertical projection of the base data, also known as a [[materialized view]] or projection index. Finding the optimal encoding method that balances (arbitrary) query performance, index size and index maintenance remains a challenge.
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| Without considering compression, Chan and Ioannidis analyzed a class of multi-component encoding methods and came to the conclusion that two-component encoding sits at the kink of the performance vs. index size curve and therefore represents the best trade-off between index size and query performance.<ref name="autogenerated355"/>
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| ==Binning==
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| For high-cardinality columns, it is useful to bin the values, where each bin covers multiple values and build the bitmaps to represent the values in each bin. This approach reduces the number of bitmaps used regardless of encoding method.<ref>{{cite book |chapter = Space efficient bitmap indexing| title= Proceedings of the ninth international conference on Information and knowledge management (CIKM '00) | year=2000 | author =N. Koudas | publisher = ACM | location = New York, NY, USA | pages = 194–201 | doi=10.1145/354756.354819 }}</ref> However, binned indexes can only answer some queries without examining the base data. For example, if a bin covers the range from 0.1 to 0.2, then when the user asks for all values less than 0.15, all rows that fall in the bin are possible hits and have to be checked to verify whether they are actually less than 0.15. The process of checking the base data is known as the candidate check. In most cases, the time used by the candidate check is significantly longer than the time needed to work with the bitmap index. Therefore, binned indexes exhibit irregular performance. They can be very fast for some queries, but much slower if the query does not exactly match a bin.
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| ==History==
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| The concept of bitmap index was first introduced by Professor Israel Spiegler and Rafi Maayan in their research "Storage and Retrieval Considerations of Binary Data Bases", published in 1985.<ref>{{cite journal | title = Storage and retrieval considerations of binary data bases | author1 = Spiegler I | author2 = Maayan R | journal = Information Processing and Management: an International Journal | volume = 21 | issue = 3 | year = 1985 | doi = 10.1016/0306-4573(85)90108-6 | pages = 233–54 }}</ref> The first commercial database product to implement a bitmap index was Computer Corporation of America's [[Model 204]]. [[Patrick O'Neil]] published a paper about this implementation in 1987.<ref name="model204">{{cite conference | last = O'Neil | first = Patrick | title = Model 204 Architecture and Performance | booktitle = Proceedings of the 2nd International Workshop on High Performance Transaction Systems | pages = 40–59 | publisher = Springer-Verlag | year = 1987 | location = London, UK | editor = Dieter Gawlick, Mark N. Haynie, and Andreas Reuter (Eds.) }}</ref> This implementation is a hybrid between the basic bitmap index (without compression) and the list of Row Identifiers (RID-list). Overall, the index is organized as a [[B+tree]]. When the column cardinality is low, each leaf node of the B-tree would contain long list of RIDs. In this case, it requires less space to represent the RID-lists as bitmaps. Since each bitmap represents one distinct value, this is the basic bitmap index. As the column cardinality increases, each bitmap becomes sparse and it may take more disk space to store the bitmaps than to store the same content as RID-lists. In this case, it switches to use the RID-lists, which makes it a [[B+tree]] index.<ref>{{cite conference | title=Bit-sliced index arithmetic | booktitle= Proceedings of the 2001 ACM SIGMOD international conference on Management of data (SIGMOD '01) | year = 2001 | author = D. Rinfret, P. O'Neil and E. O'Neil | editor = Timos Sellis (Ed.) | publisher = ACM | location = New York, NY, USA | pages = 47–57 | doi = 10.1145/375663.375669 }}</ref><ref>{{cite conference | author = E. O'Neil, P. O'Neil, K. Wu | title = Bitmap Index Design Choices and Their Performance Implications | booktitle = 11th International Database Engineering and Applications Symposium (IDEAS 2007) | year = 2007 | pages = 72–84 | url=http://crd.lbl.gov/~kewu/ps/LBNL-62756.pdf | isbn = 0-7695-2947-X | doi = 10.1109/IDEAS.2007.19 }}</ref>
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| ==In-memory bitmaps==
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| One of the strongest reasons for using bitmap indexes is that the intermediate results produced from them are also bitmaps and can be efficiently reused in further operations to answer more complex queries. Many programming languages support this as a bit array data structure. For example, Java has the <code>[http://download.oracle.com/javase/6/docs/api/java/util/BitSet.html BitSet]</code> class.
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| Some database systems that do not offer persistent bitmap indexes use bitmaps internally to speed up query processing. For example, [[PostgreSQL]] versions 8.1 and later implement a "bitmap index scan" optimization to speed up arbitrarily complex [[logical operation]]s between available indexes on a single table.
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| For tables with many columns, the total number of distinct indexes to satisfy all possible queries (with equality filtering conditions on either of the fields) grows very fast, being defined by this formula:
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| <math> \mathbf{C}_n^\left [ \frac{n}{2} \right ] \equiv \frac{n!}{(n-\left [ \frac{n}{2} \right ])! \left [ \frac{n}{2} \right ]!}</math>.<ref>{{cite web|author=Alex Bolenok|date=2009-05-09|title=Creating indexes|url=http://explainextended.com/2009/05/09/creating-indexes/}}</ref>
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| <ref>{{cite web|author=Egor Timoshenko|title=On minimal collections of indexes|url=http://explainextended.com/files/index-en.pdf }}</ref> | |
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| A bitmap index scan combines expressions on different indexes, thus requiring only one index per column to support all possible queries on a table.
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| Applying this access strategy to B-tree indexes can also combine range queries on multiple columns. In this approach, a temporary in-memory bitmap is created with one [[bit]] for each row in the table (1 [[MiB]] can thus store over 8 million entries). Next, the results from each index are combined into the bitmap using [[bitwise operation]]s. After all conditions are evaluated, the bitmap contains a "1" for rows that matched the expression. Finally, the bitmap is traversed and matching rows are retrieved. In addition to efficiently combining indexes, this also improves [[locality of reference]] of table accesses, because all rows are fetched sequentially from the main table.<ref>{{cite web |author=Tom Lane |date=2005-12-26 |title=Re: Bitmap indexes etc. |publisher=PostgreSQL mailing lists |url=http://archives.postgresql.org/pgsql-performance/2005-12/msg00623.php |accessdate=2007-04-06 }}</ref> The internal bitmap is discarded after the query. If there are too many rows in the table to use 1 bit per row, a "lossy" bitmap is created instead, with a single bit per disk page. In this case, the bitmap is just used to determine which pages to fetch; the filter criteria are then applied to all rows in matching pages.
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| ==References==
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| ;Notes
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| {{Reflist|30em}}
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| ;Bibliography
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| *{{Cite journal|last=O'Connell|first=S.|year=2005|title=Advanced Databases Course Notes|location=[[Southampton]]|publisher=[[University of Southampton]]|postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}
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| *{{Cite journal|last1=O'Neil|first1=P.|last2=O'Neil|first2=E.|year=2001|title=Database Principles, Programming, and Performance|location=[[San Francisco]]|publisher=[[Morgan Kaufmann Publishers]]|postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}
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| *{{Cite journal|last1=Zaker|first1=M.|last2=Phon-Amnuaisuk|first2=S.|last3=Haw|first3=S.C.|year=2008|issue=2|volume=2|title=An Adequate Design for Large Data Warehouse Systems: Bitmap index versus B-tree index|journal=[[International Journal of Computers and Communications]]|url=http://www.universitypress.org.uk/journals/cc/cc-21.pdf|accessdate=2010-01-07|postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}
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| {{DEFAULTSORT:Bitmap Index}}
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| [[Category:Bit data structures|Index]]
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| [[Category:Data management]]
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| [[Category:Database index techniques]]
| |
The Fujifilm Instax mini 8 can be a basic compact digital video camera which will take fast photos and increases them as an old style Polaroid camera. The analogue video camera seems like a stuffed toy and and is also sure to have major hipster attraction.
When we finally reside in a community the location where the prefers of Hipstamatic and Instragram reigns supreme, the Instax micro 8 is a bit more pleasurable way to get that vintage snapshot appearance.
Obtainable in 5 various colors (bright white, yellow, blue colored and pink black colored), the Instax mini 8 appears like a large boys and girls gadget by reviewing the matte plastic material complete, chunky camera lens and big control buttons. Regardless of its hulking measurement in comparison to today’s stream-lined camcorders, the Instax smaller 8 weighs about just 307g as well as being 10% leaner than past Instax styles. It’s mild enough to toss in a tote while not issues, regardless that it's not quite pants pocket-pleasant.
Control keys boasting are essential. At the start is often a option to increase the collapsible zoom lens and start up the camera. Across the camera lens could be the lumination correction call you could style to find the fujifilm instax mini film (http://www.fujifilminstaxmini8.info/fujifilm-instax-mini) different direct exposure quantities. On the hand traction may be the cameras lead to along with the viewfinder over along with the usually on flash just alongside it. About the backside is how you’ll locate spaces for video and also the battery pack around the fingers traction. Without a doubt it does take power packs, two AA types being exact. It becomes an analogue digital camera in each way.
Primarily this really is a digicam with simple principles; to help you to capture images while using ideal degree of lumination. There is 5 diverse direct exposure amounts to pick from; Inside the house, Night-time (F12.7), Gloomy, Hue (F16), Warm, Somewhat gloomy (F22), Sun-drenched and brilliant (F32). Additionall, there’s a completely new Great Essential option to capture photos with serious degrees of brightness and also a gentler atmosphere.
There is no there's and autofocus a taking pictures choice of .6m to 2.7m, so you should get up close. The flash includes a reuse period of .2-6 seconds and there exists a repaired shutter speed of 1/one minute.
The Instax smaller 8 just uses Fuji Instax motion picture which comes in packs of 10 and measure 62 by 46mm. That is about the magnitude of a credit card, so these snap shots take the tiny measurement. Packages can cost approximately £15 doing the smaller 8 a high priced purchase eventually.
To use pictures you just demand twist the dial towards the appropriate publicity amount, peer from the viewfinder and take your picture. It's as easy as that. Images can take a moment to completely produce and effects might be merged.
There is no space for fault and if you achieve it bad, being exposed concentrations and colours look away. Worst of all, you’ve thrown away among those high-priced films.
Lacking autofocus truly helps it be challenging to nail the images first time. Visuals are impressively thorough and produce the soft colour results to produce that old, Polaroid-design and style appearance, when you get it proper. Having pics of men and women will work primarily properly, but it will take a little more work to photograph terrific vistas photos or simple images of stuff.
In the 5 various publicity options, the Sunny, Marginally Cloud option creates essentially the most satisfying photographs. There's fantastic details inside the background and foreground with a good shade variety.
Photos inside can take a little bit more job and it's on this page with the possible lack of aim definitely illustrates. Shapes and colours look far too rinsed out and impression lucidity is just not good, while the usually-on flash can help replace with reduced-lit up situations.
Needless to say, photographs are saved to the small area, but you do possess the big bright border at the base which means you can sign or depart a note allow it that pleasant individual impression.
Should you prefer a break through the megapixels along with the luxurious of having the ability to vacant trash pictures towards a reuse container, the Fujifilm Instax mini 8 cameras quite a bit of pleasurable. Should you are able to complement the correct direct exposure quantities together with the proper setting, it's very simple to use, and you will record some good quality images.
It provides its apparent limitations. It runs on battery power along with the movies work out very pricey after you take into account the quantity of pictures you are likely to screw up. Whenever you can admit that it is planning to amount to eventually and like the idea of owning something is not really information about adding pics to Myspace, the Instax small 8 digital camera is a amazing, classic-fashioned high-end camera that lovers of Polaroids fujifilm instax mini 8 amazon (her explanation) will cherish.
It may possibly also develop a entertaining, basic way to introduce children to pictures.
Verdict
The Fujifilm Instax mini 8 is really an quick digicam that’s user-friendly and its a memo in the days or weeks well before digicams. The motion picture is pricey, but if you want to change the clock again, this can be a terrific retro snapper to accomplish it with.