indexing

问题 My data structure is like this: firebase-endpoint/updates/<location_id>/<update_id> each location has many updates that firebase adds as "array" elements. How can I index on the "validFrom" property of each update if the location_id is unknown before insertion into the databse? { "rules": { "updates": { "<location_id>": { // WHAT IS THIS NODE SUPPOSED TO BE? ".indexOn": ["validFrom"] } } } } data structure sample { "71a57e17cbfd0f524680221b9896d88c5ab400b3": { "-KBHwULMDZ4EL_B48-if": { "place

问题 My data structure is like this: firebase-endpoint/updates/<location_id>/<update_id> each location has many updates that firebase adds as "array" elements. How can I index on the "validFrom" property of each update if the location_id is unknown before insertion into the databse? { "rules": { "updates": { "<location_id>": { // WHAT IS THIS NODE SUPPOSED TO BE? ".indexOn": ["validFrom"] } } } } data structure sample { "71a57e17cbfd0f524680221b9896d88c5ab400b3": { "-KBHwULMDZ4EL_B48-if": { "place

问题 mongoose: 5.8.9 node: v12.13.0 After setting up to create index on the schema, mongoose doesn't create the index, After creating a new document there is only ID index nothing newly created. I had done as the document mentioned for creating index but still I can't figure out where I'm making the mistake. When const ads = await Ad.find({ $text: { $search: "something" } }) Error MongoError: text index required for $text query at Connection.<anonymous> (/home/usama/Projects/commercial/adex/node

问题 mongoose: 5.8.9 node: v12.13.0 After setting up to create index on the schema, mongoose doesn't create the index, After creating a new document there is only ID index nothing newly created. I had done as the document mentioned for creating index but still I can't figure out where I'm making the mistake. When const ads = await Ad.find({ $text: { $search: "something" } }) Error MongoError: text index required for $text query at Connection.<anonymous> (/home/usama/Projects/commercial/adex/node

问题 mongoose: 5.8.9 node: v12.13.0 After setting up to create index on the schema, mongoose doesn't create the index, After creating a new document there is only ID index nothing newly created. I had done as the document mentioned for creating index but still I can't figure out where I'm making the mistake. When const ads = await Ad.find({ $text: { $search: "something" } }) Error MongoError: text index required for $text query at Connection.<anonymous> (/home/usama/Projects/commercial/adex/node

问题 mongoose: 5.8.9 node: v12.13.0 After setting up to create index on the schema, mongoose doesn't create the index, After creating a new document there is only ID index nothing newly created. I had done as the document mentioned for creating index but still I can't figure out where I'm making the mistake. When const ads = await Ad.find({ $text: { $search: "something" } }) Error MongoError: text index required for $text query at Connection.<anonymous> (/home/usama/Projects/commercial/adex/node

问题 At the risk of being a bit off-topic, I want to show a simple solution for loading large csv files in a dask dataframe where the option sorted=True can be applied and save a significant time of processing. I found the option of doing set_index within dask unworkable for the size of the toy cluster I am using for learning and the size of the files (33GB). So if your problem is loading large unsorted CSV files, ( multiple tens of gigabytes ), into a dask dataframe and quickly start performing

问题 I have a Pandas DataFrame which has a list of integers inside one of the columns. I'd like to access the individual elements within this list. I've found a way to do it by using tolist() and turning it back into a DataFrame , but I am wondering if there is a simpler/better way. In this example, I add Column A to the middle element of the list in Column B . import pandas as pd df = pd.DataFrame({'A' : (1,2,3), 'B': ([0,1,2],[3,4,5,],[6,7,8])}) df['C'] = df['A'] + pd.DataFrame(df['B'].tolist())

问题 I have two DataFrames . One looks like this: df1.head() #CHR Start End Name chr1 141474 173862 SAP chr1 745489 753092 ARB chr1 762988 794826 SAS chr1 1634175 1669127 ETH chr1 2281853 2284259 BRB And the second DataFrame looks as follows: df2.head() #chr start end chr1 141477 173860 chr1 745500 753000 chr16 56228385 56229180 chr11 101785507 101786117 chr7 101961796 101962267 I am looking to map the first three columns from two DataFrames and create a new DataFrame , df3 . For example, if #chr

问题 Can anyone help me with finding an algorithm to change a position of a node in a linked list according to the input? Example: I have the linked list: 1->2->3->4->END and the user chose the second node and the index 4. The algorithm will give us the result: 1->3->4->2->END. Thanks for your help! 回答1: It is really easy to move nodes in a linked list because they are done for that... To change a node's position, just change it's next pointer to the next node address, and the previous node's next