partitioning

问题 I need to reorder a sorted list so the "middle" element is the highest number. The numbers leading up to the middle are incremental, the numbers past the middle are in decreasing order. I have the following working solution, but have a feeling that it can be done simpler: foo = range(7) bar = [n for i, n in enumerate(foo) if n % 2 == len(foo) % 2] bar += [n for n in reversed(foo) if n not in bar] bar [1, 3, 5, 6, 4, 2, 0] 回答1: how about: foo[len(foo)%2::2] + foo[::-2] In [1]: foo = range(7)

问题 I need to reorder a sorted list so the "middle" element is the highest number. The numbers leading up to the middle are incremental, the numbers past the middle are in decreasing order. I have the following working solution, but have a feeling that it can be done simpler: foo = range(7) bar = [n for i, n in enumerate(foo) if n % 2 == len(foo) % 2] bar += [n for n in reversed(foo) if n not in bar] bar [1, 3, 5, 6, 4, 2, 0] 回答1: how about: foo[len(foo)%2::2] + foo[::-2] In [1]: foo = range(7)

问题 I'm trying to implement a program that returns the number of existing partitions of an integer n as part of an assignment. I wrote the code below, but it returns the wrong number (Partitions n returns the result of Partitions n-1). I don't get why this happens. I've tried many things and still don't know how to fix it, can anyone please help me? [edited code out to avoid plagiarism from my colleagues :p] m stands for the biggest number allowed in a partition, so partition(4,4) would be 5 = 4,

问题 Using AWS::Glue::Table, you can set up an Athena table like here. Athena supports partitioning data based on folder structure in S3. I would like to partition my Athena table from my Glue template. From AWS Glue Table TableInput, it appears that I can use PartitionKeys to partition my data, but when I try to use the below template, Athena fails and can't get any data. Resources: ... MyGlueTable: Type: AWS::Glue::Table Properties: DatabaseName: !Ref MyGlueDatabase CatalogId: !Ref AWS:

问题 I'm trying to sum a column up to the current row (in SQL Server). How do I do this? select t1.CounterTime, t1.StartTime, t1.EndTime, isNull(t1.value, 0) as value1, -- How do I make Total1 the sum of t1.value over all previous rows? sum( isNull(t1.value, 0) ) over (partition by t1.CounterTime order by t1.CounterTime) as Total1 from SomeTable t1 order by t1.CounterTime But I got the partition by wrong... ╔═══╦═════════════════════════╦═════════════════════════╦═════════════════════════╦════════

问题 I'm trying to create a table which takes dates of when a employee is sick and create a new column to provide a "sickness ID", which will identify a unique instance of absence over several dates. I've managed to do this, however I now need to factor in a table which contains the working pattern of each employee, which will let me know if someone was due in work on a given day of the week. This can be joined using the day_no column in both tables along with the employee_number . I posted a this

问题 I'm trying to create a table which takes dates of when a employee is sick and create a new column to provide a "sickness ID", which will identify a unique instance of absence over several dates. I've managed to do this, however I now need to factor in a table which contains the working pattern of each employee, which will let me know if someone was due in work on a given day of the week. This can be joined using the day_no column in both tables along with the employee_number . I posted a this

问题 I created table t1 in Oracle 12c. Table has data and it is partitioned on list partition and also has subpartitions. Now I want to delete whole table and all associated partitions (and subpartitions). Is this the right command to delete all? DROP TABLE t1 PURGE; 回答1: When you run DROP then the table is removed entirely from database, i.e. the table does not exist anymore. If you just want to remove all data from that table run truncate table T1 drop storage; You can also truncate single (sub-

问题 I have a code which is suppose to group a list of transaction objects into 2 categories; public class Transaction { public String type; public Integer amount; } The following function divided the list into 2 categories by checking a condition. The output map of the stream operation is Map<Boolean, List<Transaction>> , but I would like to use a String as its key. So I converted them manually. public static Map<String, List<Transaction>> partitionTransactionArray(List<Transaction> t1) { Map

问题 When I use reduceByKey or aggregateByKey , I'm confronted with partition problems. ex) reduceBykey(_+_).map(code) Especially, if input data is skewed, the partitioning problem becomes even worse when using the above methods. So, as a solution to this, I use repartition method. For example, http://dev.sortable.com/spark-repartition/ is similar. This is good for partition distribution, but the repartition is also expensive. Is there a way to solve the partition problem wisely? 回答1: You are