indexing

问题 can someone explain me what this line means: insert <TableNameX> select *,%%bmk%% from<TableNameX> i saw a question about the same but cannot understand what it means. can someone explain what is this %%bmk%%? p/s - the insert and the From , is the same table . the Line appeard while dropping and creating indexes on - TableNameX. 回答1: It's the bulk loading of data associated with SQL Server Reindex operation 来源： https://stackoverflow.com/questions/32176351/unkown-query-insert-tablenamex

问题 Collection c has hundred thousands of documents, and every document has two fields ( x and y ). Below are some examples. { "_id" : ObjectId("53fecab45ae4ec5280a0736f"), "x" : 1, "y" : 1 } { "_id" : ObjectId("53fecab45ae4ec5280a07370"), "x" : 2, "y" : 1 } { "_id" : ObjectId("53fecab45ae4ec5280a07371"), "x" : 3, "y" : 1 } { "_id" : ObjectId("53fecab45ae4ec5280a07372"), "x" : 3, "y" : 2 } { "_id" : ObjectId("53fecab45ae4ec5280a07373"), "x" : 3, "y" : 3 } { "_id" : ObjectId(

问题 My previous question discovered that the cause of my performance troubles is because using the indexed distance operator in Postgis is very slow on large areas that return many rows. As a result, it seems the ideal solution may be to pick some arbitrary miles distance amount and then use the indexed distance operator ( ST_DWithin ) when it's in that range (let's say, below 75 miles), and then to use the non-indexed distance operator ( <-> ) when it's above that range (so, 75 miles or above)

问题 My previous question discovered that the cause of my performance troubles is because using the indexed distance operator in Postgis is very slow on large areas that return many rows. As a result, it seems the ideal solution may be to pick some arbitrary miles distance amount and then use the indexed distance operator ( ST_DWithin ) when it's in that range (let's say, below 75 miles), and then to use the non-indexed distance operator ( <-> ) when it's above that range (so, 75 miles or above)

问题 Setup I'm using Single Table Inheritance (STI) in Rails simplified to the following: class Vehicle belongs_to :user end class Car < Vehicle end class Plane < Vehicle end Each record in the vehicles table will have a type column set to either 'Car' or 'Plane' in addition to the user_id foreign key. It could also have additional values if more vehicle types are added, however, type will always have a much lower cardinality than user_id . Just as in real life, I expect this table to contain many

问题 I'm using ElasticSearch 7.1.1 as a full-text search engine. At the beginning all the documents are accessible to every user. I want to give users the possibility to edit documents. The modified version of the document will be accessible only to the editor and everyone else will only be able to see the default document. To do this I will add two array to every document: An array of users excluded from seeing the doc An array with the only user that can see the this doc Every time someone edit

问题 sqlite> .schema movie CREATE TABLE movie ( id INTEGER PRIMARY KEY, title TEXT, year INTEGER, nth TEXT, for_video BOOLEAN ); sqlite> select count(*) from movie; count(*) ---------- 530256 sqlite> For query, Which years in human history have seen at least one movie released? $ sqlite movie.db sqlite> select DISTINCT year from movie order by year asc; sqlite> select * from sqlite_master where type='index'; index|index1|movie|194061|CREATE INDEX index1 on movie (year) sqlite> .quit $ $ time

问题 I need to extract one element from each column of a matrix according to an index vector. Say: index = [0,1,1] matrix = [[1,4,7],[2,5,8],[3,6,9]] Index vector tells me I need the first element from column 1, second element from column 2, and third element from column 3. The output should be [1,5,8] . How can I write it out without explicit loop? Thanks 回答1: You can use advanced indexing: index = np.array([0,1,2]) matrix = np.array([[1,4,7],[2,5,8],[3,6,9]]) res = matrix[np.arange(matrix.shape

问题 I have some results that I put in a data frame. I have some factor columns and many numeric columns. I can easily convert the numeric columns to numeric with indexing, as per the answer to this question. #create example data df = data.frame(replicate(1000,sample(1:10,1000,rep=TRUE))) df$X1 = LETTERS[df$X1] df$X2 = LETTERS[df$X2] df$X3 = LETTERS[df$X3] df[-1] <- sapply(df[-1], function(x) ifelse(runif(length(x)) < 0.1, NA, x)) #find columns that are factors factornames = c("X1", "X2", "X3")

问题 Basically I'm trying to get a "rankings" between 4 people. I have an array of player scores which contains the scores of each person such that person 1's score is at index 0, person 2's score is at index 1, etc... I want to obtain the index of the top scorer in the list and get the second, and the third, and the last. My attempt at the solution: I made a list out of the array playerScores (I feel like it might not be necessary, but due to what I'm about to do, I didn't want to ruin the