indexing

问题 I stumbled upon with a very curious case. We have a SQL Server 2012 database and such a table CREATE TABLE [dbo].[ActiveTransactions] ( [Id] [BIGINT] IDENTITY(1,1) NOT NULL, [Amount] [DECIMAL](12, 4) NOT NULL, [TypeId] [SMALLINT] NOT NULL, [GameProviderId] [SMALLINT] NULL, [UserId] [INT] NOT NULL, [Checksum] [NVARCHAR](150) NOT NULL, [Date] [DATETIME2](7) NOT NULL, [ExternalKey] [VARCHAR](60) NULL, [ExternalDescription] [NVARCHAR](1000) NULL, [OperatorId] [SMALLINT] NULL, [GameId] [NVARCHAR]

问题 I stumbled upon with a very curious case. We have a SQL Server 2012 database and such a table CREATE TABLE [dbo].[ActiveTransactions] ( [Id] [BIGINT] IDENTITY(1,1) NOT NULL, [Amount] [DECIMAL](12, 4) NOT NULL, [TypeId] [SMALLINT] NOT NULL, [GameProviderId] [SMALLINT] NULL, [UserId] [INT] NOT NULL, [Checksum] [NVARCHAR](150) NOT NULL, [Date] [DATETIME2](7) NOT NULL, [ExternalKey] [VARCHAR](60) NULL, [ExternalDescription] [NVARCHAR](1000) NULL, [OperatorId] [SMALLINT] NULL, [GameId] [NVARCHAR]

问题 Can anybody suggest a good C++ library for storing Multi-dimensional Sparse Matrix that focuses on the compression of data in matrix. The number of dimensions of the matrix will be huge (say, 80 dimensions). Any help is most welcome :). EDIT: The matrix is highly sparse, in the order of 0.0000001 (or) 1x10 -6 . 回答1: In c# I have used key value pairs or "dictionaries" to store sparse populated arrays. I think for 80 dimensions you would have to construct a string based key. Use a single

问题 Can anybody suggest a good C++ library for storing Multi-dimensional Sparse Matrix that focuses on the compression of data in matrix. The number of dimensions of the matrix will be huge (say, 80 dimensions). Any help is most welcome :). EDIT: The matrix is highly sparse, in the order of 0.0000001 (or) 1x10 -6 . 回答1: In c# I have used key value pairs or "dictionaries" to store sparse populated arrays. I think for 80 dimensions you would have to construct a string based key. Use a single

问题 I am working with potentially huge XML files containing complex trace information from on of my projects. I would like to build indexes for those XML files so that one can quickly find sub sections of the XML document without having to load it all into memory. If I have created a "shelve" index that could contains information like "books for author Joe" are at offsets [22322, 35446, 54545] then I can just open the xml file like a regular text file and seek to those offsets and then had that

问题 I need a new Mongo collection that associates data with an IP address, the address being the collection key. I'm wondering if there's any performance advantage using the decimal notation of the IP adress (e.g. 3299551096 as an integer) instead of the dotted notation (e.g. "198.252.206.16" as a string). I haven't found any evidence for or against, nor any performance comparison between integer and string indexes. Is there any reason to prefer one over the other? 回答1: An integer value storage

问题 I have an array of numbers, and the maximum value might occurrence more than once. Is it possible to find the index of the last occurrence of the maximum value by using something like numpy.argmax? Or, even better, is it possible to get a list of indices of all the occurrences of the maximum value in the array? 回答1: import numpy as np a = np.array((1,2,3,2,3,2,1,3)) occurences = np.where(a == a.max()) # occurences == array([2, 4, 7]) 来源： https://stackoverflow.com/questions/7038975/numpy

问题 Is there a notable difference in query performance, if the index is set on datetime type column, instead of boolean type column (and querying is done on that column)? In my current design I got 2 columns: is_active TINYINT(1), indexed deleted_at DATETIME query is SELECT * FROM table WHERE is_active = 1; Would it be any slower, if I made an index on deleted_at column instead, and ran queries like this SELECT * FROM table WHERE deleted_at is null; ? 回答1: Here is a MariaDB (10.0.19) benchmark

问题 I'm trying to debug a very strange discrepency between 2 seperate cosmos db collection that on face value are configured the same. We recently modified some code that executed the following query. OLD QUERY SELECT * FROM c WHERE c.ProductId = "CODE" AND c.PartitionKey = "Manufacturer-GUID" NEW QUERY SELECT * FROM c WHERE (c.ProductId = "CODE" OR ARRAY_CONTAINS(c.ProductIdentifiers, "CODE")) AND c.PartitionKey = "Manufacturer-GUID" The introduction of that Array_Contains call in the production

问题 Hi I'm trying to implement CoreSpotlight in my app. When indexing do I need to run this every time or is it sufficient to run this once when app is installed for the first time? If app is deleted do I need to index again? Here's the code I'm using: - (void)spotLightIndexing { NSString *path = [[NSBundle mainBundle] pathForResource: @"aDetailed" ofType:@"plist"]; NSDictionary *plistDict = [[NSDictionary alloc] initWithContentsOfFile:path]; NSArray *plistArray = [plistDict allKeys]; for (id key