Is there a built-in way to index and access indices of individual elements of DataStream/DataSet collection?
Like in typical Java collections, where you know that e.g. a 3rd element of an ArrayList can be obtained by ArrayList.get(2) and vice versa ArrayList.indexOf(elem) gives us the index of (the first occurence of) the specified element. (I'm not asking about extracting elements out of the stream.)
More specifically, when joining DataStreams/DataSets, is there a "natural"/easy way to join elements that came (were created) first, second, etc.?
I know there is a zipWithIndex transformation that assigns sequential indices to elements. I suspect the indices always start with 0? But I also suspect that they aren't necessarily assigned in the order the elements were created in (i.e. by their Event Time). (It also exists only for DataSets.)
This is what I currently tried:
DataSet<Tuple2<Long, Double>> tempsJoIndexed = DataSetUtils.zipWithIndex(tempsJo);
DataSet<Tuple2<Long, Double>> predsLinJoIndexed = DataSetUtils.zipWithIndex(predsLinJo);
DataSet<Tuple3<Double, Double, Double>> joinedTempsJo = tempsJoIndexed
.join(predsLinJoIndexed).where(0).equalTo(0)...
And it seems to create wrong pairs.
I see some possible approaches, but they're either non-Flink or not very nice:
I could of course assign an index to each element upon the stream's
creation and have e.g. a stream of Tuples.
Work with event-time timestamps. (I suspect there isn't a way to key by timestamps, and even if there was, it wouldn't be useful for
joining multiple streams like this unless the timestamps are
actually assigned as indices.)
We could try "collecting" the stream first but then we wouldn't be using Flink anymore.
The 1. approach seems like the most viable one, but it also seems redundant given that the stream should by definition be a sequential collection and as such, the elements should have a sense of orderliness (e.g. `I'm the 36th element because 35 elements already came before me.`).
I think you're going to have to assign index values to elements, so that you can partition the data sets by this index, and thus ensure that two records which need to be joined are being processed by the same sub-task. Once you've done that, a simple groupBy(index) and reduce() would work.
But assigning increasing ids without gaps isn't trivial, if you want to be reading your source data with parallelism > 1. In that case I'd create a RichMapFunction that uses the runtimeContext sub-task id and number of sub-tasks to calculate non-overlapping and monotonic indexes.
How would I go about selecting the nth values of an array and adding them to another array.
For example, if i have an NSArray which has 100 objects and I want to add every 5th object? I understand how to select the 5th object and how to add to a new array etc, but just looking for the best way to do this. This is for image manipulation, so will be dealing with arrays of up to 2m pixel values.
Is the best way to just use for loops?
You can using striding:
.stride(to: 100, by: 5)
So to create a new array:
Array(0.stride(to: 10, by: 2).map( { myArray[$0] }))
UPDATE: As Leo Dabus points out, the above will start at element 0 (and take every 2nd). If you want to start at the 5th and take every 5th, you would use:
Array(4.stride(to: 100, by: 5).map( { myArray[$0] }))
Using loops is pretty good: they are easy to read, and they are about as efficient as anything else that you may want to use for this purpose. The only optimization to the for loop approach is to reserve a specific number of elements upfront, because you know how many elements you are going to write.
If you are going to make the same selection from multiple arrays (e.g. processing an array of arrays), consider creating NSIndexSet, and applying it with objectsAtIndexes to perform the selection. This may give your code slightly better readability, because the for loop for creating indexes would be separate from the process of selection.
Finally, if you need to optimize for speed, and your arrays store wrapped primitives, consider using plain arrays instead of NSArray to avoid wrapping and unwrapping. This has a potential of giving you the most improvement, because by eliminating additional memory accesses for unwrapping it would also significantly improve locality of reference, which has crucial importance for cache use optimization.
I successfully amended the nice CloudBalancing example to include the fact that I may only have a limited number of computers open at any given time (thanx optaplanner team - easy to do). I believe this is referred to as a bounded-space problem. It works dandy.
The processes come in groupwise, say 20 processes in a given order per group. I would like to amend the example to have optaplanner also change the order of these groups (not the processes within one group). I have therefore added a class ProcessGroup in the domain with a member List<Process>, the instances of ProcessGroup being stored in a List<ProcessGroup>. The desired optimisation would shuffle the members of this List, causing the instances of ProcessGroup to be placed at different indices of the List List<ProcessGroup>. The index of ProcessGroup should be ProcessGroup.index.
The documentation states that "if in doubt, the planning entity is the many side of the many-to-one relationsship." This would mean that ProcessGroup is the planning entity, the member index being a planning variable, getting assigned to (hopefully) different integers. After every new assignment of indices, I would have to resort the list List<ProcessGroup in ascending order of ProcessGroup.index. This seems very odd and cumbersome. Any better ideas?
Thank you in advance!
Philip.
The current design has a few disadvantages:
It requires 2 (genuine) entity classes (each with 1 planning variable): probably increases search space (= longer to solve, more difficult to find a good or even feasible solution) + it increases configuration complexity. Don't use multiple genuine entity classes if you can avoid it reasonably.
That Integer variable of GroupProcess need to be all different and somehow sequential. That smelled like a chained planning variable (see docs about chained variables and Vehicle Routing example), in which case the entire problem could be represented as a simple VRP with just 1 variable, but does that really apply here?
Train of thought: there's something off in this model:
ProcessGroup has in Integer variable: What does that Integer represent? Shouldn't that Integer variable be on Process instead? Are you ordering Processes or ProcessGroups? If it should be on Process instead, then both Process's variables can be replaced by a chained variable (like VRP) which will be far more efficient.
ProcessGroup has a list of Processes, but that a problem property: which means it doesn't change during planning. I suspect that's correct for your use case, but do assert it.
If none of the reasoning above applies (which would surprise me) than the original model might be valid nonetheless :)
As an aid to learning objective c/oop, I'm designing an iOS app to store and display periodic bodyweight measurements. I've got a singleton which returns a mutablearray of the shared store of measurement object. Each measurement will have at least a date and a body weight, and I want to be able to add historic measurements.
I'd like to display the measurements in date order. What's the best way to do this? As far as I can see the options are as follows: 1) when adding a measurement - I override addobject to sort the shared store every time after a measurement is added, 2) when retrieving the mutablearray I sort it, or 3) I retrieve the mutablearray in whatever order it happens to be in the shared store, then sort it when displaying the table/chart.
It's likely that the data will be retrieved more frequently than a new datum is added, so option 1 will reduce redundant sorting of the shared store - so this is the best way, yes?
You can use a modified version of (1). Instead of sorting the complete array each time a new object is inserted, you use the method described here: https://stackoverflow.com/a/8180369/1187415 to insert the new object into the array at the correct place.
Then for each insert you have only a binary search to find the correct index for the new object, and the array is always in correct order.
Since you said that the data is more frequently retrieved than new data is added, this seems to be more efficient.
If I forget your special case, this question is not so easy to answer. There are two basic solutions:
Keep array unsorted and when you try to access the element and array is not sorted, then sort it. Let's call it "lazy sorting".
Keep array sorted when inserting elements. Note this is not about appending new element at the end and then sort the whole array. This is about finding where the element should be (binary search) and place it there. Let's call it "sorted insert".
Both techniques are correct and useful and deciding which one is better depends on your use cases.
Example:
You want to insert hundreds of elements into the array, then access the elements, then again insert hundreds of elements, then access. In summary, you will be inserting values in big chunks. In this case, lazy sorting will be better.
You will often insert individual elements and you will access the elements often. Then sorted insert will have better performance.
Something in the middle (between inserting 1 and inserting tens of elements). You probably don't care which one of the methods will be used.
(Note that you can use also specialized structures to keep an array sorted, not based on NSArray, e.g. structures based on a balanced tree, while keeping number of elements in the subtree).
I have a collection of objects in a database. Images in a photo gallery, products in a catalog, chapters in a book, etc. Each object is represented as a row. I want to be able to arbitrarily order these images, storing that ordering in the database so when I display the objects, they will be in the right order.
For example, let's say I'm writing a book, and each chapter is an object. I write my book, and put the chapters in the following order:
Introduction, Accessibility, Form vs. Function, Errors, Consistency, Conclusion, Index
It goes to the editor, and comes back with the following suggested order:
Introduction, Form, Function, Accessibility, Consistency, Errors, Conclusion, Index
How can I store this ordering in the database in a robust, efficient way?
I've had the following ideas, but I'm not thrilled with any of them:
Array. Each row has an ordering ID, when order is changed (via a removal followed by an insertion), the order IDs are updated. This makes retrieval easy, since it's just ORDER BY, but it seems easy to break.
// REMOVAL
UPDATE ... SET orderingID=NULL WHERE orderingID=removedID
UPDATE ... SET orderingID=orderingID-1 WHERE orderingID > removedID
// INSERTION
UPDATE ... SET orderingID=orderingID+1 WHERE orderingID > insertionID
UPDATE ... SET orderID=insertionID WHERE ID=addedID
Linked list. Each row has a column for the id of the next row in the ordering. Traversal seems costly here, though there may by some way to use ORDER BY that I'm not thinking of.
Spaced array. Set the orderingID (as used in #1) to be large, so the first object is 100, the second is 200, etc. Then when an insertion happens, you just place it at (objectBefore + objectAfter)/2. Of course, this would need to be rebalanced occasionally, so you don't have things too close together (even with floats, you'd eventually run into rounding errors).
None of these seem particularly elegant to me. Does anyone have a better way to do it?
An other alternative would be (if your RDBMS supports it) to use columns of type array. While this breaks the normalization rules, it can be useful in situations like this. One database which I know about that has arrays is PostgreSQL.
The acts_as_list mixin in Rails handles this basically the way you outlined in #1. It looks for an INTEGER column called position (of which you can override to name of course) and using that to do an ORDER BY. When you want to re-order things you update the positions. It has served me just fine every time I've used it.
As a side note, you can remove the need to always do re-positioning on INSERTS/DELETES by using sparse numbering -- kind of like basic back in the day... you can number your positions 10, 20, 30, etc. and if you need to insert something in between 10 and 20 you just insert it with a position of 15. Likewise when deleting you can just delete the row and leave the gap. You only need to do re-numbering when you actually change the order or if you try to do an insert and there is no appropriate gap to insert into.
Of course depending on your particular situation (e.g. whether you have the other rows already loaded into memory or not) it may or may not make sense to use the gap approach.
If the objects aren't heavily keyed by other tables, and the lists are short, deleting everything in the domain and just re-inserting the correct list is the easiest. But that's not practical if the lists are large and you have lots of constraints to slow down the delete. I think your first method is really the cleanest. If you run it in a transaction you can be sure nothing odd happens while you're in the middle of the update to screw up the order.
Just a thought considering option #1 vs #3: doesn't the spaced array option (#3) only postpone the problem of the normal array (#1)? Whatever algorithm you choose, either it's broken, and you'll run into problems with #3 later, or it works, and then #1 should work just as well.
I did this in my last project, but it was for a table that only occasionally needed to be specifically ordered, and wasn't accessed too often. I think the spaced array would be the best option, because it reordering would be cheapest in the average case, just involving a change to one value and a query on two).
Also, I would imagine ORDER BY would be pretty heavily optimized by database vendors, so leveraging that function would be advantageous for performance as opposed to the linked list implementation.
Use a floating point number to represent the position of each item:
Item 1 -> 0.0
Item 2 -> 1.0
Item 3 -> 2.0
Item 4 -> 3.0
You can place any item between any other two items by simple bisection:
Item 1 -> 0.0
Item 4 -> 0.5
Item 2 -> 1.0
Item 3 -> 2.0
(Moved item 4 between items 1 and 2).
The bisection process can continue almost indefinitely due to the way floating point numbers are encoded in a computer system.
Item 4 -> 0.5
Item 1 -> 0.75
Item 2 -> 1.0
Item 3 -> 2.0
(Move item 1 to the position just after Item 4)
Since I've mostly run into this with Django, I've found this solution to be the most workable. It seems that there isn't any "right way" to do this in a relational database.
I'd do a consecutive number, with a trigger on the table that "makes room" for a priority if it already exists.
I had this problem as well. I was under heavy time pressure (aren't we all) and I went with option #1, and only updated rows that changed.
If you swap item 1 with item 10, just do two updates to update the order numbers of item 1 and item 10. I know it is algorithmically simple, and it is O(n) worst case, but that worst case is when you have a total permutation of the list. How often is that going to happen? That's for you to answer.
I had the same issue and have probably spent at least a week concerning myself about the proper data modeling, but I think I've finally got it. Using the array datatype in PostgreSQL, you can store the primary key of each ordered item and update that array accordingly using insertions or deletions when your order changes. Referencing a single row will allow you to map all your objects based on the ordering in the array column.
It's still a bit choppy of a solution but it will likely work better than option #1, since option 1 requires updating the order number of all the other rows when ordering changes.
Scheme #1 and Scheme #3 have the same complexity in every operation except INSERT writes. Scheme #1 has O(n) writes on INSERT and Scheme #3 has O(1) writes on INSERT.
For every other database operation, the complexity is the same.
Scheme #2 should not even be considered because its DELETE requires O(n) reads and writes. Scheme #1 and Scheme #3 have O(1) DELETE for both read and write.
New method
If your elements have a distinct parent element (i.e. they share a foreign key row), then you can try the following ...
Django offers a database-agnostic solution to storing lists of integers within CharField(). One drawback is that the max length of the stored string can't be greater than max_length, which is DB-dependent.
In terms of complexity, this would give Scheme #1 O(1) writes for INSERT, because the ordering information would be stored as a single field in the parent element's row.
Another drawback is that a JOIN to the parent row is now required to update ordering.
https://docs.djangoproject.com/en/dev/ref/validators/#django.core.validators.validate_comma_separated_integer_list