indexing

问题 I want to store enum values in MongoDB collection. Can I effectively store them as strings? Will it affect index performance in comparison with enum values as ints? Does Mongo indexer optimize string indexes in the case when they contain only few fixed options as string values, to achieve speed similar to querying index by sorted integer? 回答1: Storing enum values in MongoDB as strings is perfectly fine, and yes, if you index the field I'd expect the performance to be comparable to indexed

问题 I want a easy to read access to some parts of a multidimensional numpy array. For any array accessing the first dimension is easy ( b[index] ). Accessing the sixth dimension on the other hand is "hard" (especially to read). b[:,:,:,:,:,index] #the next person to read the code will have to count the : Is there a better way to do this? Especially is there a way, where the axis is not known while writing the program? Edit: The indexed dimension is not necessarily the last dimension 回答1: If you

问题 I'm interested in the multi-dimensional case of Increment Numpy array with repeated indices. I have an N-dimensional array and a set N index arrays, who's values I want to increment. The index arrays might have have repeated entries. Without repeats, the solution is a = arange(24).reshape(2,3,4) i = array([0,0,1]) j = array([0,1,1]) k = array([0,0,3]) a[i,j,k] += 1 With repeats, (ex. j=array([0,0,2]) ), I'm unable to make numpy increment the replicates. 回答1: How about this: import numpy as np

问题 How can I use a variable as index in django template? Right now I get this error: Exception Type: TemplateSyntaxError Exception Value: Could not parse the remainder: '[year]' from 'bikesProfit.[year]' I also tried {{ bikesProfit.year }} but this gives an empty result. {% for year in years_list %} <tr> <th>Total profit {{ year }}:</th> </tr> <tr> <th></th> <th> {{ bikesProfit[year] }} </th> ... 回答1: It's a very common question, there are a lot of answers on SO. You can make custom template

问题 I have an array of values, t, that is always in increasing order (but not always uniformly spaced). I have another single value, x. I need to find the index in t such that t[index] is closest to x. The function must return zero for x < t.min() and the max index (or -1) for x > t.max(). I've written two functions to do this. The first one, f1, is MUCH quicker in this simple timing test. But I like how the second one is just one line. This calculation will be done on a large array, potentially

问题 Is there a method in Java to get the list of objects from an Arraylist to another ArrayList, by just specifying the start and end index? 回答1: Yes you can use the subList method: List<...> list2 = list1.subList(startIndex, endIndex); This returns a view on that part of the original list, it does not copy the data. If you want a copy: List<...> list2 = new ArrayList<...> (list1.subList(startIndex, endIndex)); 回答2: /create an ArrayList object ArrayList arrayList = new ArrayList(); //Add elements

问题 Which option is better and faster? Insertion of data after creating index on empty table or creating unique index after inserting data. I have around 10M rows to insert. Which option would be better so that I could have least downtime. 回答1: Insert your data first, then create your index. Every time you do an UPDATE, INSERT or DELETE operation, any indexes on the table have to be updated as well. So if you create the index first, and then insert 10M rows, the index will have to be updated 10M

问题 I'm sensing some weird pandas behavior here. I have a dataframe that looks like df = pd.DataFrame(columns=['Col 1', 'Col 2', 'Col 3'], index=[('1', 'a'), ('2', 'a'), ('1', 'b'), ('2', 'b')]) In [14]: df Out[14]: Col 1 Col 2 Col 3 (1, a) NaN NaN NaN (2, a) NaN NaN NaN (1, b) NaN NaN NaN (2, b) NaN NaN NaN I can set the value of an arbitrary element In [15]: df['Col 2'].loc[('1', 'b')] = 6 In [16]: df Out[16]: Col 1 Col 2 Col 3 (1, a) NaN NaN NaN (2, a) NaN NaN NaN (1, b) NaN 6 NaN (2, b) NaN

问题 Consider the following table: Column | Type | --------------------+--------------------------+ id | bigint | creation_time | timestamp with time zone | ... Queries like the following (let alone more complicated JOINs) takes quite a while, because they needs to calculate creation_time::DATE for each item: SELECT creation_time::DATE, COUNT(*) FROM items GROUP BY 1; How do I create an index on the day part of the timestamp - creation_time::DATE ? I have tried: CREATE INDEX items_day_of_creation

问题 I'm building a index which is just several sets of ordered 32 bit integers stored continuously in a binary file. The problem is that this file grows pretty large. I've been thinking of adding some compressions scheme but that's a bit out of my expertise. So I'm wondering, what compression algorithm would work best in this case? Also, decompression has to be fast since this index will be used to make make look ups. 回答1: If you are storing integers which are close together (eg: 1, 3 ,4, 5, 9,