Natural way of indexing elements in Flink - indexing

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.

Related

Fast, efficient method of assigning large array of data to array of clusters?

I'm looking for a faster, more efficient method of assigning data gathered from a DAQ to its proper location in a large cluster containing arrays of subclusters.
My current method 1 relies heavily on the OpenG cluster manipulation tools, but with a large data-set the performance is far too slow.
The array and cluster location of each element of data from the DAQ is determined during an initialization phase and doesn't change during acquisition.
Because the data element origin and end points are the same throughout acquisition, I would think an array of memory locations could be created and the data directly assigned to its proper place. I'm just not sure how to implement such a thing.
The following code does what you want:
For each of your cluster elements (AMC, ANLG_PM and PA) you should add a case in the string case structure, for the elements AMC and PA you will need to place a second case structure.
This is really more of a comment, but I do not have the reputation to leave those yet, so here it is:
Regarding adding cases for every possible value of Array name, is there any reason why you cannot use an enum here? Since you are placing it into a cluster anyway, I would suggest making a type-defined enum of your possible array names. That way, when you want to add or remove one, you only have to do it in one place.
You will still need to right-click on your case structures that use this enum and select Add item for every value if you are adding a value, or manually delete the obsolete value if you are removing one. I suppose some maintenance is required either way...

Keeping an array sorted - at setting, getting or later?

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).

Redis Sorted Sets: How do I get the first intersecting element?

I have a number of large sorted sets (5m-25m) in Redis and I want to get the first element that appears in a combination of those sets.
e.g I have 20 sets and wanted to take set 1, 5, 7 and 12 and get only the first intersection of only those sets.
It would seem that a ZINTERSTORE followed by a "ZRANGE foo 0 0" would be doing a lot more work that I require as it would calculate all the intersections then return the first one. Is there an alternative solution that does not need to calculate all the intersections?
There is no direct, native alternative, although I'd suggest this:
Create a hash which its members are your elements. Upon each addition to one of your sorted sets, increment the relevant member (using HINCRBY). Of course, you'll make the increment only after you check that the element does not exist already in the sorted set you are attempting to add to.
That way, you can quickly know which elements appear in 4 sets.
UPDATE: Now that I rethink about it, it might be too expensive to query your hash to find items with value of 4 (O(n)). Another option would be creating another Sorted Set, which its members are your elements, and their score gets incremented (as I described before, but using ZINCRBY), and you can quickly pull all elements with score 4 (using ZRANGEBYSCORE).

Which data type to use for ordinal?

Whenever I have some records/objects that I want to be in a certain order, I usually create a field called Ordinal.
I often wonder if it would be better to use an integer or a decimal value for the ordinal field.
This is a consideration when moving an object to a different position in the order:
If you use consecutive integers, you have to do some serious reworking of all of the ordinals (or at least the ordinals that fall before the original position of the object being moved).
If you use integers but space them out (maybe at 1000 intervals), then you can just change the ordinal to a mid point value between the surrounding objects where you want to move the object. This could fail if somewhere down the line you end up with consecutive integers.
If you use decimal numbers you could just find the average of the surround object's ordinals and use that for the object to be moved.
Maybe it would be possible to use a string, but I could see that getting pretty goofy.
I'm sure there are other considerations I haven't thought of.
What do you use and why?
"This could fail if somewhere down the line you end up with consecutive integers."
For this (probably rare and thus not performance important) case, you could implement a renumber method that spaces out again. When I used to program in COMAL (anyone know that language?), you could do this very thing with line numbers.
Decimals seem to solve your problem pretty well. Since Decimals are just base 10 floats, you actually have a lot of digits available. Unless you've seen cases where you've gotten out to quite a few digits and had reason to suspect a reason for an unlimited number of digits being necessary, I'd let it ride.
If you really need an alternative and don't see a need to stick with a basic data bype, you might go with tumbler arithmetic. The basic idea is that it's a place notation that is infinitely expandable at each position. Pretty simple conceptually.
I used to use a decimal type for a field of this kind to order records in a table, which we actually exposed to the customer so that they could set their own order. Although it sounds cheesy our customers liked it; they found it very intuitive. They caught on very quickly that they could use numbers like 21.5 to move something between 21 and 22.
Maybe it's because they were accountants.
I use integers and just rearrange as necessary when a new item needs to be inserted in the middle of the order. Since you can create the necessary gap with a single update statement, it's fairly trivial. However, I've only ever done this on lookup tables of a few dozen rows at most, obviously this scales a bit poorly. But I would say that if you need a solution to this problem for a large number of rows, the process(es) for maintaining the order should be proceduralized anyway, which makes the choice of data type largely moot.
I remember this being a similar question to a previous post. It can be found here:
SQL Server Priority Ordering
The linked list would still work, but this is a much easier solution if you don't want to track a parent child relationship.
Sounds like what you want is a linked list. That way you always know what comes next and you don't have to guess. So the position field would be a pointer to the object following it.
The problem I have always had with using arbitrary numbers for position, is that it can quickly fall to entropy. What if more items get added and the number become consecutive etc. etc. It can quickly become unmanageable if the list of items changes position.
To implement this in sql server table, add another field with the same data type as the primary key. If the field is null then it is the bottom element in the list. If you are storing multiple lists in the same table you will probably want to add another field called ListID which designates all rows with the same ListID pertain to the same list. So something like this.
Table:
ID INT
ListID INT
Child INT
Pararent Row For first list:
1, 1, 2
First Child
2, 1, 3
Second Child
3, 1, NULL
Parent Row for second list:
4, 2, 5
First Child
5, 2, 6
Second Child
6, 2, NULL
You'll probably have to do an insert and an update every time you add a row, which can be a little tedious, but it will always make the list line up.
Is the "certain order" based on data outside of the table? If so, why not include it so you can do the sorting dynamically? If it's already in the table, adding a field is redundant.

Represent Ordering in a Relational Database

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