indexing

问题 Given the update to pandas 0.20.0 and the deprecation of .ix, I am wondering what the most efficient way to get the same result using the remaining .loc and .iloc . I just answered this question, but the second option (not using .ix ) seems inefficient and verbose. Snippet: print df.iloc[df.loc[df['cap'].astype(float) > 35].index, :-1] Is this the proper way to go when using both conditional and index position filtering? 回答1: You can stay in the world of a single loc by getting at the index

问题 In MySQL, how to build index to speed up this query? SELECT c1, c2 FROM t WHERE c3='foobar'; 回答1: To really give a answer it would be useful to see if you have existing indexes already, but... All this is assuming table 't' exists and you need to add an index and you only currently have a single index on your primary key or no indexes at all. A covering index for the query will give best performance for your needs, but with any index you sacrifice some insertion speed. How much that sacrifice

问题 Given a matrix: [,1] [,2] [1,] 0 0.0 [2,] -1 0.8 What is the quickest way in R to iterate over the matrix and return the position of all non-zero entries as an index? 回答1: Here is one approach mat = matrix(rnorm(9), 3, 3) which(mat !=0, arr.ind = T) 回答2: m <- matrix(c(0, 1, 1, 0), nrow = 2) which(m != 0) or maybe which(m != 0, TRUE) 来源： https://stackoverflow.com/questions/6522134/r-return-position-of-element-in-matrix

问题 Given a matrix: [,1] [,2] [1,] 0 0.0 [2,] -1 0.8 What is the quickest way in R to iterate over the matrix and return the position of all non-zero entries as an index? 回答1: Here is one approach mat = matrix(rnorm(9), 3, 3) which(mat !=0, arr.ind = T) 回答2: m <- matrix(c(0, 1, 1, 0), nrow = 2) which(m != 0) or maybe which(m != 0, TRUE) 来源： https://stackoverflow.com/questions/6522134/r-return-position-of-element-in-matrix

问题 This is a question that I've had forever. As far as I know the order of indices matter. So an index like [first_name, last_name] is not the same as [last_name, first_name] , right? If I only define the first index, does it mean that it will only used for SELECT * FROM table WHERE first_name="john" AND last_name="doe"; and not for SELECT * FROM table WHERE last_name="doe" AND first_name="john"; Since I am using a ORM, I have no idea in which order these columns are going to be called. Does

问题 I'm just about to write a query that includes a WHERE isok=1 . As the name implies, isok is a boolean field (actually a TINYINT(1) UNSIGNED that is set to 0 or 1 as needed). Is there any performance gain in indexing this field? Would the engine (InnoDB in this case) perform better or worse looking up the index? 回答1: Not really. You should think about it like a book. If there were only 3 kinds of words in a book and you index all of them, you would have the same number of index pages as normal

问题 I'm just about to write a query that includes a WHERE isok=1 . As the name implies, isok is a boolean field (actually a TINYINT(1) UNSIGNED that is set to 0 or 1 as needed). Is there any performance gain in indexing this field? Would the engine (InnoDB in this case) perform better or worse looking up the index? 回答1: Not really. You should think about it like a book. If there were only 3 kinds of words in a book and you index all of them, you would have the same number of index pages as normal

问题 If I have data in my users collection that looks like: { name: '...', email: '...', ..., photos: { 123: { url: '...', title: '...', ... }, 456: { url: '...', title: '...', ... }, ... } } And I want to find which user owns photo id 127, then I am using the query: db.users.find( {'photos.127': {'$exists' => true} } ); I've tried, but it doesn't seem possible to get MongoDB to use an index for this query. The index I tried was: db.users.ensureIndex({photos:1}); . And when I used explain() mongo

问题 Let me start by saying I have looked at many similar questions asked, but all of them relate to Timestamp and DateTime field type without indexing. At least that is my understanding. As we all know, there are certain advantages when it comes to DateTime. Putting them aside for a minute, and assuming table's engine is InnoDB with 10+ million records , which query would perform faster when criteria is based on: DateTime with index int with index In other words, it is better to store date and

问题 I have a problem with a dynamic list in Excel 2003 where some cells that I want to be empty are returning #NUM! . I have tried manipulating the following code, but to no avail: =IF(ISERROR(INDEX(venue_name, SMALL(IF(($A$10=date_ns)*(COUNTIF($A$13:A29,venue_name)=0), ROW(date_ns)-MIN(ROW(date_ns))+1, ""), 1))) I know its something to do with syntax/parentheses but have exhausted myself trying different combinations. Without the IF(ISERROR( and the closing bracket, the code runs absolutely fine