large-data | 易学教程

How to store extremely large numbers?

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问题 For example I have a factorial program that needs to save really huge integers that can be 50+ digits long. The absolute maximum primitive data type in C++ is unsigned long long int with a maximum value 18446744073709551615 which is only 20 digits long. Here\'s the link to the limits of C++: http://www.cplusplus.com/reference/climits/ How do I store numbers that are larger than that in a variable of some sort? 回答1: If you already have a boost dependency (which many people these days do), you

How to plot with a png as background? [duplicate]

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问题 This question already has answers here : Overlay data onto background image (3 answers) Closed 2 years ago . This question was migrated from Cross Validated because it can be answered on Stack Overflow. Migrated 7 years ago . I made a plot with a 3 million points and saved it as PNG. It took a few hours and I would like to avoid re-drawing all the points. How can I generate a new plot that has this PNG as a background? 回答1: Try this: library(png) #Replace the directory and file information

SELECT COUNT() vs mysql_num_rows();

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问题 I have a large table (60+) millions of records. I\'m using PHP script to navigate through this table. PHP script (with pagination) loads very fast because: The table engine is InnoDB thus SELECT COUNT() is very slow and mysql_num_rows() is not an option, so i keep the total row count (the number that i use to generate pagination) in a separate table (i update this record total_rows=total_rows-1 and total_rows=total_rows1+1 during DELETE and INSERT ). But the question is what to do with the

Memory-constrained external sorting of strings, with duplicates combined&counted, on a critical server (billions of filenames)

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问题 Our server produces files like {c521c143-2a23-42ef-89d1-557915e2323a}-sign.xml in its log folder. The first part is GUID; the second part is name template. I want to count the number of files with same name template. For instance, we have {c521c143-2a23-42ef-89d1-557915e2323a}-sign.xml {aa3718d1-98e2-4559-bab0-1c69f04eb7ec}-hero.xml {0c7a50dc-972e-4062-a60c-062a51c7b32c}-sign.xml The result should be sign.xml,2 hero.xml,1 The total kinds of possible name templates is unknown, possibly exceeds

How to read only lines that fulfil a condition from a csv into R?

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问题 This question was migrated from Cross Validated because it can be answered on Stack Overflow. Migrated 5 years ago . I am trying to read a large csv file into R. I only want to read and work with some of the rows that fulfil a particular condition (e.g. Variable2 >= 3 ). This is a much smaller dataset. I want to read these lines directly into a dataframe, rather than load the whole dataset into a dataframe and then select according to the condition, since the whole dataset does not easily fit

Shared memory in multiprocessing

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问题 I have three large lists. First contains bitarrays (module bitarray 0.8.0) and the other two contain arrays of integers. l1=[bitarray 1, bitarray 2, ... ,bitarray n] l2=[array 1, array 2, ... , array n] l3=[array 1, array 2, ... , array n] These data structures take quite a bit of RAM (~16GB total). If i start 12 sub-processes using: multiprocessing.Process(target=someFunction, args=(l1,l2,l3)) Does this mean that l1, l2 and l3 will be copied for each sub-process or will the sub-processes

“Large data” work flows using pandas

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问题 I have tried to puzzle out an answer to this question for many months while learning pandas. I use SAS for my day-to-day work and it is great for it\'s out-of-core support. However, SAS is horrible as a piece of software for numerous other reasons. One day I hope to replace my use of SAS with python and pandas, but I currently lack an out-of-core workflow for large datasets. I\'m not talking about \"big data\" that requires a distributed network, but rather files too large to fit in memory

Shared memory in multiprocessing

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I have three large lists. First contains bitarrays (module bitarray 0.8.0) and the other two contain arrays of integers. l1=[bitarray 1, bitarray 2, ... ,bitarray n] l2=[array 1, array 2, ... , array n] l3=[array 1, array 2, ... , array n] These data structures take quite a bit of RAM (~16GB total). If i start 12 sub-processes using: multiprocessing.Process(target=someFunction, args=(l1,l2,l3)) Does this mean that l1, l2 and l3 will be copied for each sub-process or will the sub-processes share these lists? Or to be more direct, will I use 16GB or 192GB of RAM? someFunction will read some