How do I sort 1GB of data?

How do I sort 1GB of data?

Assume 1GB = 1024MB, so we follow following steps.

1. Divide the source file into 5 small temporary files each of size 200MB (i.e., equal to the size of ram).
2. Sort these temporary files one bye one using the ram individually (Any sorting algorithm : quick sort, merge sort).

Which sorting technique can be used to sort huge GB of data in an Organisation with limited main memory available?

External sorting is a class of sorting algorithms that can handle massive amounts of data. External sorting is required when the data being sorted do not fit into the main memory of a computing device (usually RAM) and instead they must reside in the slower external memory, usually a hard disk drive.

Can merge sort work with large dataset?

Merge sort can operate well on any type of data sets whether it is large or small. On the contrary, the quick sort cannot work well with large datasets. Quick sort is faster than merge sort in some cases such as for small data sets. Merge sort requires additional memory space to store the auxiliary arrays.

How do I sort large amounts of data?

1. For sorting a very large file , we can use external sorting technique.External sorting is an algorithm that can handle massive amounts of data.
2. using external merge sort.
3. For sorting a very large file , we can use external sorting technique.External sorting is an algorithm that can handle massive amounts of data.

Which sorting technique will be most appropriate to sort 1GB?

You have to sort 1 GB of data with only 100 MB of available main memory. Which sorting technique will be most appropriate? Explanation: The data can be sorted using external sorting which uses merging technique.

How do I sort 10 GB files?

For sorting 10 GB of data using only 1 GB of RAM:

1. Read 1 GB of the data in main memory and sort by using quicksort.
2. Write the sorted data to disk.
3. Repeat steps 1 and 2 until all of the data is in sorted 1GB chunks (there are 10 GB / 1 GB = 10 chunks), which now need to be merged into one single output file.

Which sorting technique will be most appropriate to sort 1gb?

Which sorting algorithm is the slowest algorithm for large number of data?

3) Which sorting algorithm is the slowest algorithm for large number of data? Explanation:Quick sort, Heap sort and Shell sort all have best case time complexity as O(nlogn) and Bubble sort has time complexity of O(n2). So, Bubble sort is slowest.

Why is merge sort better for large data sets?

Merge sort requires more space as it creates an extra array for storing, and no matter what it will compare every item. Quick sort on the other hand does not require extra space, and doesn’t swap or compare more than necessary.

Which sort is best for large data?

Quicksort is probably more effective for datasets that fit in memory. For larger data sets it proves to be inefficient so algorithms like merge sort are preferred in that case. Quick Sort in is an in-place sort (i.e. it doesn’t require any extra storage) so it is appropriate to use it for arrays.

What do I do if my data is too big for my memory?

Possible solutions. Money-costing solution: One possible solution is to buy a new computer with a more robust CPU and larger RAM that is capable of handling the entire dataset. Or, rent a cloud or a virtual memory and then create some clustering arrangement to handle the workload.

What is the best time complexity of bubble sort?

Difference between Selection, Bubble and Insertion Sort

Selection	Bubble
Best case time complexity is O(n2)	Best case time complexity is O(n)
Works better than bubble as no of swaps are significantly low	Worst efficiency as too many swaps are required in comparison to selection and insertion
It is in-place	It is in-place

How to sort 10GB of data in 1 GB memory?

Read 100 MB of the data in main memory and sort by some conventional sorting method, like quicksort. 2. Write the sorted data to disk. 3. Repeat steps 1 and 2 until all of the data is in sorted 100 MB chunks (there are 900MB / 100MB = 9 chunks), which now need to be merged into one single output file.

How much memory is needed to sort 100 million numbers?

100 million integers of 4 bytes each occupy a little less than 400 megabytes of RAM. Even a fairly obsolete machine will now typically have at least 4 gigabytes of RAM, so if you just read the whole input into memory, sorted it, and wrote it out, you’d only use about 10% of the available memory.

How to sort million / billion 32 bit integers?

Sometimes interviewers ask how to sort million/billion 32-bit integers (e.g. here and here ). I guess they expect the candidates to compare O (N Log (N)) sort with radix sort. For million integers O (N Log (N)) sort is probably better but for billion they are probably the same. Does it make sense ?

How to sort large amounts of data in Java?

It looks like what you are looking for is external sorting. Basically, you sort small chunks of data first, write it back to the disk and then iterate over those to sort all. You can read the files in smaller parts, sort these and write them to temporrary files.