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The actual selectivity is really 1/3 for this query, because every F-150 is a Ford. This kind of estimation error can be large in some data sets. Detecting statistical correlations like this is a very computationally expensive problem, so the default behavior is to assume independence even though that may introduce some amount of error into the cardinality estimation process. Filtered Statistics solves this problem by capturing the conditional probability for the MODEL column when the MAKE value is Ford. While using this solution requires a lot of statistics objects, it can be effective to x the most important cases in an application where cardinality estimation error is causing poorly performing plans to be chosen by the Query Optimizer, especially when the WHERE clause has a relatively small number of distinct values. In additional to the Independence assumption, the Query Optimizer contains other assumptions that are used to both simplify the estimation process and to be consistent in how estimates are made across all operators. Another assumption in the Query Optimizer is the Uniformity assumption. This means that if a range of values is being considered but they are not known, then they are assumed to be uniformly distributed over the range in which they exist. For example, if a query has an IN list with different parameters for each value, the values of the parameters are assumed not to be grouped. The nal assumption in the Query Optimizer is the Containment assumption. This says that if a range of values is being joined with another range of values, then the default assumption is that that query is being asked because those ranges overlap and qualify rows. Without this assumption, many common queries would be underestimated and poor plans would be chosen.

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javascript - How to create a QR code reader in a HTML5 website ...
There aren't many JavaScript decoders. ... At some point I may post the stripped-down reverse-engineered QR reader, but in the meantime have some fun ...

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Scanning & Reading QR Code Barcodes in Java Class. Easy to integrate QR Code barcode reading and scanning feature in your Java applications; Complete ...

SQL Server 2005 introduced a feature to improve cardinality estimation for strings called String Statistics or Trie Trees. SQL Server histograms can have up to 200 steps, or unique values, to store information about the overall distribution of a table. While this works well for many numeric types, the string data types often have many more unique values as well as numerous functions that depend more heavily on a deeper statistical understanding of the type, such as LIKE. Two hundred unique values is often not suf cient to provide accurate cardinality estimates for strings, and storing lots of strings outside of the table can use a lot of space. Trie trees were created to store a sample of the strings in a column in a space-ef cient manner.

The trie tree is not documented, but generally trie trees work as follows: If we have a column containing the following values:

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How to Write and Read QR Code with ZXing in Java - Code Pool
17 Aug 2015 ... In this post, I'd like to share how to use ZXing to create QR code writer and reader for both desktop Java applications and Android mobile apps.

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QR Code Write and Read Program in Java: ... FileNotFoundException; import java.io. .... ScanForBarcodes(Bitmap bitmap) { // initialize a new Barcode reader.

bution and future releases, may charge for the second release of the software Freeware may be used, but not resold FTP (File Transfer Protocol) Used for transferring files between two computers across the Internet

The trie tree for this structure is shown in Figure 8-26.

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16 Feb 2018 ... The ZXing (“zebra crossing”) is an open-source, multi-format 1D/2D barcode image processing library implemented in Java , with ports to other languages.

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Curiously your code works for me, but I had to remove the follow hint. tmpHintsMap.put(DecodeHintType.PURE_BARCODE, Boolean.FALSE);. When my image ...

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SQL Server actually stores a sample of the strings in the column, and even this is bound to take up not too much space. SQL Server also has some idea of the relative frequency for each substring listed in the trie tree. Overall, this provides the ability to store far more than 200 unique substrings worth of frequency information.

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