indexing

问题 I'am new to Apache Lucene, I'm using Apache Lucene 8.4.1, I can do Lucene Indexing and Searching but don't know how to read and list index / print index using java. How to get indexed fields and term list ? . I was able to get Fileds list by using following function grabbed from Other Stackoverflow article. public static String[] getFieldNames(IndexReader reader) { List<String> fieldNames = new ArrayList<String>(); //For a simple reader over only one index, reader.leaves() should only return

问题 I'am new to Apache Lucene, I'm using Apache Lucene 8.4.1, I can do Lucene Indexing and Searching but don't know how to read and list index / print index using java. How to get indexed fields and term list ? . I was able to get Fileds list by using following function grabbed from Other Stackoverflow article. public static String[] getFieldNames(IndexReader reader) { List<String> fieldNames = new ArrayList<String>(); //For a simple reader over only one index, reader.leaves() should only return

问题 I have a Postgresql 11.8 table named posts where I would like to define a column slugs of type JSONB, which would contain arrays of strings such as ["my-first-post", "another-slug-for-my-first-post"] . I can find a post having a specific slug using the ? existence operator: SELECT * FROM posts WHERE slugs ? 'some-slug' . Each post is expected to only have a handful of slugs but the amount of posts is expected to grow. Considering the above query where some-slug could be any string: How can I

问题 I have a pandas DataFrame indexed by a DatetimeIndex that holds a time series, i.e. some data as a function of time. Now I would like to plot the behavior over the day regardless of the date. To do so I drop the date: for date, group in df.groupby(by = df.index.date): # drop date group.index = group.index.timetz However, like this I lose a lot of convenience functions of a DatetimeIndex , e.g. it is no longer possible to do things like df[df.index.hour > 9] Is there a better way to drop the

问题 The following 2 series of stocks in a single excel file: Can be combined using the date as index? The result should be like this: 回答1: You need a simple df.merge() here: df = pd.merge(df1, df2, left_index=True, right_index=True, how='outer') OR df = df1.join(df2, how='outer') 回答2: I am trying this: df3 = pd.concat([df1, df2]).sort_values('Date').reset_index(drop=True) or df3 = df1.append(df2).sort_values('Date').reset_index(drop=True) 来源： https://stackoverflow.com/questions/64212463/combine

问题 I have a table containing key-value pairs which I would like to be ale to search efficiently on: SELECT * WHERE meta_key = "User ID" AND meta_value = "123userId"; However due to a legacy requirement the key and value NVARCHAR storage might be as large as 255 and 1000 characters respectively. Indexing on such large columns is not only costly but also outright restricted on some db types. I believe MySQL has a system to allow indexes by a LEFT -style substring as follows: CREATE INDEX ix

问题 I am trying to read in a comma separated text file into Python with read_csv . However, Python is taking the header and shifting it over to the right by one. Data file example with less columns than I actually have: (example file with more data: https://www.dropbox.com/s/5glujwqux6d0msh/test.txt?dl=0) DAY,TIME,GENVEG,LATI,LONGI,AREA,CHEM 226, 1200, 2, -0.5548999786D+01, 0.3167600060D+02, 0.1000000000D+07, NaN 226, 1115, 2, -0.1823500061D+02, 0.3668500137D+02, 0.1000000000D+07, NaN If I try

问题 I'm trying to change all values in the slice except the first one but it does not work... what am i doing wrong ? print(test) test.loc[(test.col_1==-5)&(test.index>'2018-07-17 13:00:00')&(test.index<'2018-07-17 14:00:00'),['col_1']][1:]=-1 print(test) provides the below output 17/07/2018 13:51:00 -5 17/07/2018 13:52:00 -1 17/07/2018 13:53:00 -5 17/07/2018 13:54:00 -5 17/07/2018 13:55:00 -5 17/07/2018 13:56:00 -5 17/07/2018 13:57:00 -5 17/07/2018 13:58:00 -5 17/07/2018 13:59:00 -5 17/07/2018

问题 My issue is that if I reassign an item in a list such that the reassignment happens during a parallel process, then after the parallel processes are finished, the change reverts back to its original state. In the below example- greatly simplified for ease of understanding-, I have a function that changes the list element NoZeros[0] to "chicken" and a second function that changes NoZeros[1] to "sandwich". I even put "global" in the second function just to demonstrate that this isn't a local vs

问题 How do search engines such as Lucene, etc. perform AND queries where a term is common to many documents in the dataset? For example, in an inverted index of: term | document_id --------------------- program | 1, 2, 3, 5... python | 1, 4 code | 4 c++ | 4, 5 the term program is present in several documents meaning a query of program AND code would require performing an intersection upon a very large set of documents. Is there a way to perform AND queries without having to take the intersection