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)"Introduction"The Bron filter (Bloom filter) was proposed by Bron in 1970. It is actually a very long binary vector and a series of random mapping functions .The Bron filter can be used to retrieve whether an element is in a collection.Its advantage is that space efficiency and query time are far more than the general algorithm, the disadvantage is that there is a certain rate of error recognition and removal difficulties ."How it Works"Let's explain how it works by using the example above for

. The current line looks for characters FX, FX, TX, TX4. Basic Replacement: S/S1/S2 (replace the next S1 with S2)5. Replace All:%S/S1/S26. Replace the current line only: s/s1/s2/g7. Replace some lines: n1,n2 s/s1/s2/g8, search mode for/string, search for the next n, search for the previous n9, make bookmarks MX, but do not see bookmark tags, and can only use lowercase letters10. Move to the key next to ' x,1 ' at a label11. Move to the location where

the "Vim window split screen" in the article, you already know how to split the window. In fact, I do not use the splitter window command, but instead use the browse file command to separate the window. Such as: Split the current window up and down and browse the directory below: :Hex 全称为 :Hexplore （在下边分屏浏览目录） If you want to be on top, you're in: Add one behind the He! :He! （在上分屏浏览目录） If you want to split the screen right and left, you can do this: :Ve 全称为 :Vexplore （在左边分屏间浏览目录，要在右边则是 :Ve!）

: Print("error:func gettrainscheduleinfo Select_items_from_url failed.url =%s, flag =%s"%(trainschedule))returnTrainbaseinfo3. Parse the return dataThe return data is a JSON type of string, directly json.loads, parsing can#get all the information you want to checkAlltrainresultdic = {}#Train Query Result collection forTrainscheduleinchTrainschedulelist:trainbaseinfo= Self.gettrainscheduleinfo (Trainschedule)#JSON string ##----Test---- # Trainbaseinfo = "{

The Prum filter principle is simple: is to hash a string into an integer key, and then select a very long sequence of bits, starting with 0, where the key turns 0 in this position to 1; the next time you come in a string, the value key after the hash, and if the value on this bit is 1, Then it means that the string exists. If you follow the above procedure, it is no different from the hashing algorithm, and the hashing algorithm is duplicated. The Prum filter is a string that Hashicheng multip

', ' E4 ' union Select ' E ', ' E5 ' union Select ' E ', ' E6 ' union Select ' E ', ' E7 ' union Select ' E ', ' E8 ' union Select ' E ', ' E9 ' union Select ' E ', ' E10 ' --Company 6 INSERT INTO Company Select ' F ', ' F1 ' union Select ' F ', ' F2 ' union Select ' F ', ' F3 ' union Select ' F ', ' F4 ' union Select ' F ', ' F5 ' union Select ' F ', ' F6 ' union Select ' F ', ' F7 ' union Select ' F ', ' F8 ' union Select ' F ', ' F9 ' union Select ' F ', ' F10 ' --Company

system is believed to be the current Chinese Internet companies are pursuing the goal. Wang: As an Internet technology architect, can you briefly summarize the concepts, principles, and methods of ocean Internet service technology architecture? Lin Hao went: I think ebay's five-point summary is pretty much complete: (1) "Split", the separation of the database and the application of the split, of course, this requires strong technical support, this point to achieve the goal is usually easy to ap

Prum in 1970. It is actually a very long binary vector and a series of random mapping functions. We use the above example to explain how the work works. Assuming we store 100 million e-mail addresses, we first set up a 1,600,000,002-bit, or 200 million-byte vector, and then set all 1.6 billion binaries to zero. For each email address X, we use eight different random number generator (F1,F2, ..., F8) to produce eight information fingerprints (F1, F2, ..., F8). Then use a random number generator

of random mapping functions. We use the above example to explain how the work works.Assuming we store 100 million e-mail addresses, we first set up a 1,600,000,002-bit, or 200 million-byte vector, and then set all 1.6 billion binaries to zero. For each email address X, we use eight different random number generator (F1,F2, ..., F8) to produce eight information fingerprints (F1, F2, ..., F8). Then use a random number generator G to map these eight information fingerprints to eight natural number

end of the file DG1.5other1. Display line number set Nu2. Cancel line number set Nonu3. Find content/4. Look down N5. Look up N6. Undo Current Operation U7.vim Query Help: Assist G8. Replace All content:%s#yes#no#g1.6Bulk Operations1. Bulk DeleteCtrl + V Visual block (enter bulk edit modeSelect up or DownPress D to delete2. Batch IncreaseCtrl + V Visual block (enter bulk edit modeSelect up or DownPress I to enter edit modeFor editingPress ESC to wait