data-partitioning | 易学教程

Using an iterator to Divide an Array into Parts with Unequal Size

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问题 I have an array which I need to divide up into 3-element sub-arrays. I wanted to do this with iterators, but I end up iterating past the end of the array and segfaulting even though I don't dereference the iterator . given: auto foo = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 }; I'm doing: auto bar = cbegin(foo); for (auto it = next(bar, 3); it < foo.end(); bar = it, it = next(bar, 3)) { for_each(bar, it, [](const auto& i) { cout << i << endl; }); } for_each(bar, cend(foo), [](const auto& i) { cout <<

How to partition a vector into groups of regular, consecutive sequences?

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I have a vector, such as c(1, 3, 4, 5, 9, 10, 17, 29, 30) and I would like to group together the 'neighboring' elements that form a regular, consecutive sequence in a ragged vector resulting in: L1: 1 L2: 3,4,5 L3: 9,10 L4: 17 L5: 29,30 Naive code (of an ex-C programmer): partition.neighbors <- function(v) { result <<- list() #jagged array currentList <<- v[1] #current series for(i in 2:length(v)) { if(v[i] - v [i-1] == 1) { currentList <<- c(currentList, v[i]) } else { result <<- c(result, list(currentList)) currentList <<- v[i] #next series } } return(result) } Now I understand that a) R is

U-SQL Output in Azure Data Lake

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问题 Would it be possible to automatically split a table into several files based on column values if I don't know how many different key values the table contains? Is it possible to put the key value into the filename? 回答1: This is our top ask (and has been previously asked on stackoverflow too :). We are currently working on it and hopefully have it available by summer. Until then you have to write a script generator. I tend to use U-SQL to generate the script but you could do it with Powershell

Spark SQL - Difference between df.repartition and DataFrameWriter partitionBy?

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问题 What is the difference between DataFrame repartition() and DataFrameWriter partitionBy() methods? I hope both are used to \"partition data based on dataframe column\"? Or is there any difference? 回答1: If you run repartition(COL) you change the partitioning during calculations - you will get spark.sql.shuffle.partitions (default: 200) partitions. If you then call .write you will get one directory with many files. If you run .write.partitionBy(COL) then as the result you will get as many