Why is the server response after a Drag&Drop so large and slow - vaadin-flow

I'm having some performance issues dragging cards between grids. From a backend perspective, storing the data from the grids after a change takes about 200ms.
But then, when the backend work seems to be done, it takes another 2,5 seconds for the frontend to get the response from the request. The request that's taking so long contact 2 rpc events: grid-drop and grid-dragend.
The response is also unusually large I think. Just to give you an idea, see screenshot ... notice the tiny scrollbar at the right. 🙂
TTFB is 2,42s, download size about half a MB.
Any ideas what's going on here and how I can eliminate this?
I'm using Vaadin 21.0.4, spring boot 2.5.4.
Steps I've taken to optimise performance:
Optimize db query + indexing
Use #cacheable where possible
Implemented the cards using LitElement
This is the drop listener:
ComponentEventListener<GridDropEvent<Task>> dropListener = event -> {
if (dragSource != null) {
// The item ontop or below where the source item is dropped. Used to calculate the index of the newly dropped item(s)
Optional<Task> targetItem = event.getDropTargetItem();
// if the item is dropped on an existing row and the dragged item contains the same items that's being dropped.
if (targetItem.isPresent() && draggedItems.contains(targetItem.get())) {
return;
}
// Add dragged items to the grid of the target room
Grid<Task> targetGrid = event.getSource();
Optional<Room> room = dayPlanningView.getRoomForGrid(targetGrid);
// The items of the target Grid. Using listdataview so this would not retrigger the query
List<Task> targetItems = targetGrid.getListDataView().getItems().toList();
// Calculate the position of the dropped item
int index = targetItem.map(task -> targetItems.indexOf(task)
+ (event.getDropLocation() == GridDropLocation.BELOW ? 1 : 0))
.orElse(0);
room.ifPresent(r -> service.plan(draggedItems, r, index, dayPlanningView.getSelectedDate()));
// send event to update other users
Optional<ScheduleUpdatedEvent> scheduleUpdatedEvent = room.map(r -> new ScheduleUpdatedEvent(PlanningMasterDetailView.this, r.getId()));
scheduleUpdatedEvent.ifPresent(Broadcaster::broadcast);
// remove items from the source grid. using list provider so items can be removed without DB round-trip.
productionOrderGrid.getListDataView().removeItems(draggedItems);
}
};
I'm a bit stuck now, as I'm kinda out of ideas 😦
Thanks

You should use the TemplateRenderer/LitRenderer instead of the ComponentRenderer because the generated server-side components are affecting the performance:
Read more here: https://vaadin.com/blog/top-5-most-common-vaadin-performance-pitfalls-and-how-to-avoid-them

Related

Spring-data-elasticsearch: Result window is too large (index.max_result_window)

We retrieve information from Elasticsearch 2.7.0 and we allow the user to go through the results. When the user requests a high page number we get the following error message:
Result window is too large, from + size must be less than or equal to:
[10000] but was [10020]. See the scroll api for a more efficient way
to request large data sets. This limit can be set by changing the
[index.max_result_window] index level parameter
The thing is we use pagination in our requests so I don't see why we get this error:
#Autowired
private ElasticsearchOperations elasticsearchTemplate;
...
elasticsearchTemplate.queryForPage(buildQuery(query, pageable), Document.class);
...
private NativeSearchQuery buildQuery() {
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
boolQueryBuilder.should(QueryBuilders.boolQuery().must(QueryBuilders.termQuery(term, query.toUpperCase())));
NativeSearchQueryBuilder nativeSearchQueryBuilder = new NativeSearchQueryBuilder().withIndices(DOC_INDICE_NAME)
.withTypes(indexType)
.withQuery(boolQueryBuilder)
.withPageable(pageable);
return nativeSearchQueryBuilder.build();
}
I don't understand the error because we retreive pageable.size (20 elements) everytime... Do you have any idea why we get this?
Unfortunately, Spring data elasticsearch even when paging results searchs for a much larger result window in the elasticsearch. So you have two options, the first is to change the value of this parameter.
The second is to use the scan / scroll API, however, as far as I understand, in this case the pagination is done manually, as it is used for infinite sequential reading (like scrolling your mouse).
A sample:
List<Pessoa> allItens = new ArrayList<>();
String scrollId = elasticsearchTemplate.scan(build, 1000, false, Pessoa.class);
Page<Pessoa> page = elasticsearchTemplate.scroll(scrollId, 5000L, Pessoa.class);
while (true) {
if (!page.hasContent()) {
break;
}
allItens.addAll(page.getContent());
page = elasticsearchTemplate.scroll(scrollId, 5000L, Pessoa.class);
}
This code, shows you how to read ALL the data from your index, you have to get the requested page inside scrolling.

BigQueryIO loads not offloading rows to GCS when early trigger occurs

I'm playing around with BigQueryIO write using loads. My load trigger is set to 18 hours. I'm ingesting data from Kafka with a fixed daily window.
Based on https://github.com/apache/beam/blob/v2.2.0/sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/BatchLoads.java#L213-L231 it seems that the intended behavior is to offload rows to the filesystem when at least 500k records are in a pane
I managed to produce ~ 600K records and waited for around 2 hours to see if the rows were uploaded to gcs, however, nothing was there. I noticed that the "GroupByDestination" step in "BatchLoads" shows 0 under "Output collections" size.
When I use a smaller load trigger all seems fine. Shouldn't the AfterPane.elementCountAtLeast(FILE_TRIGGERING_RECORD_COUNT)))) be triggered?
Here is the code for writing to BigQuery
BigQueryIO
.writeTableRows()
.to(new SerializableFunction[ValueInSingleWindow[TableRow], TableDestination]() {
override def apply(input: ValueInSingleWindow[TableRow]): TableDestination = {
val startWindow = input.getWindow.asInstanceOf[IntervalWindow].start()
val dayPartition = DateTimeFormat.forPattern("yyyyMMdd").withZone(DateTimeZone.UTC).print(startWindow)
new TableDestination("myproject_id:mydataset_id.table$" + dayPartition, null)
}
})
.withMethod(Method.FILE_LOADS)
.withCreateDisposition(CreateDisposition.CREATE_NEVER)
.withWriteDisposition(WriteDisposition.WRITE_APPEND)
.withSchema(BigQueryUtils.schemaOf[MySchema])
.withTriggeringFrequency(Duration.standardHours(18))
.withNumFileShards(10)
The job id is 2018-02-16_14_34_54-7547662103968451637. Thanks in advance.
Panes are per key per window, and BigQueryIO.write() with dynamic destinations uses the destination as key under the hood, so the "500k elements in pane" thing applies per destination per window.

Firebase - How to sort the data by newly added child (Swift)? [duplicate]

I'm trying to test out Firebase to allow users to post comments using push. I want to display the data I retrieve with the following;
fbl.child('sell').limit(20).on("value", function(fbdata) {
// handle data display here
}
The problem is the data is returned in order of oldest to newest - I want it in reversed order. Can Firebase do this?
Since this answer was written, Firebase has added a feature that allows ordering by any child or by value. So there are now four ways to order data: by key, by value, by priority, or by the value of any named child. See this blog post that introduces the new ordering capabilities.
The basic approaches remain the same though:
1. Add a child property with the inverted timestamp and then order on that.
2. Read the children in ascending order and then invert them on the client.
Firebase supports retrieving child nodes of a collection in two ways:
by name
by priority
What you're getting now is by name, which happens to be chronological. That's no coincidence btw: when you push an item into a collection, the name is generated to ensure the children are ordered in this way. To quote the Firebase documentation for push:
The unique name generated by push() is prefixed with a client-generated timestamp so that the resulting list will be chronologically-sorted.
The Firebase guide on ordered data has this to say on the topic:
How Data is Ordered
By default, children at a Firebase node are sorted lexicographically by name. Using push() can generate child names that naturally sort chronologically, but many applications require their data to be sorted in other ways. Firebase lets developers specify the ordering of items in a list by specifying a custom priority for each item.
The simplest way to get the behavior you want is to also specify an always-decreasing priority when you add the item:
var ref = new Firebase('https://your.firebaseio.com/sell');
var item = ref.push();
item.setWithPriority(yourObject, 0 - Date.now());
Update
You'll also have to retrieve the children differently:
fbl.child('sell').startAt().limitToLast(20).on('child_added', function(fbdata) {
console.log(fbdata.exportVal());
})
In my test using on('child_added' ensures that the last few children added are returned in reverse chronological order. Using on('value' on the other hand, returns them in the order of their name.
Be sure to read the section "Reading ordered data", which explains the usage of the child_* events to retrieve (ordered) children.
A bin to demonstrate this: http://jsbin.com/nonawe/3/watch?js,console
Since firebase 2.0.x you can use limitLast() to achieve that:
fbl.child('sell').orderByValue().limitLast(20).on("value", function(fbdataSnapshot) {
// fbdataSnapshot is returned in the ascending order
// you will still need to order these 20 items in
// in a descending order
}
Here's a link to the announcement: More querying capabilities in Firebase
To augment Frank's answer, it's also possible to grab the most recent records--even if you haven't bothered to order them using priorities--by simply using endAt().limit(x) like this demo:
var fb = new Firebase(URL);
// listen for all changes and update
fb.endAt().limit(100).on('value', update);
// print the output of our array
function update(snap) {
var list = [];
snap.forEach(function(ss) {
var data = ss.val();
data['.priority'] = ss.getPriority();
data['.name'] = ss.name();
list.unshift(data);
});
// print/process the results...
}
Note that this is quite performant even up to perhaps a thousand records (assuming the payloads are small). For more robust usages, Frank's answer is authoritative and much more scalable.
This brute force can also be optimized to work with bigger data or more records by doing things like monitoring child_added/child_removed/child_moved events in lieu of value, and using a debounce to apply DOM updates in bulk instead of individually.
DOM updates, naturally, are a stinker regardless of the approach, once you get into the hundreds of elements, so the debounce approach (or a React.js solution, which is essentially an uber debounce) is a great tool to have.
There is really no way but seems we have the recyclerview we can have this
query=mCommentsReference.orderByChild("date_added");
query.keepSynced(true);
// Initialize Views
mRecyclerView = (RecyclerView) view.findViewById(R.id.recyclerView);
mManager = new LinearLayoutManager(getContext());
// mManager.setReverseLayout(false);
mManager.setReverseLayout(true);
mManager.setStackFromEnd(true);
mRecyclerView.setHasFixedSize(true);
mRecyclerView.setLayoutManager(mManager);
I have a date variable (long) and wanted to keep the newest items on top of the list. So what I did was:
Add a new long field 'dateInverse'
Add a new method called 'getDateInverse', which just returns: Long.MAX_VALUE - date;
Create my query with: .orderByChild("dateInverse")
Presto! :p
You are searching limitTolast(Int x) .This will give you the last "x" higher elements of your database (they are in ascending order) but they are the "x" higher elements
if you got in your database {10,300,150,240,2,24,220}
this method:
myFirebaseRef.orderByChild("highScore").limitToLast(4)
will retrive you : {150,220,240,300}
In Android there is a way to actually reverse the data in an Arraylist of objects through the Adapter. In my case I could not use the LayoutManager to reverse the results in descending order since I was using a horizontal Recyclerview to display the data. Setting the following parameters to the recyclerview messed up my UI experience:
llManager.setReverseLayout(true);
llManager.setStackFromEnd(true);
The only working way I found around this was through the BindViewHolder method of the RecyclerView adapter:
#Override
public void onBindViewHolder(final RecyclerView.ViewHolder holder, int position) {
final SuperPost superPost = superList.get(getItemCount() - position - 1);
}
Hope this answer will help all the devs out there who are struggling with this issue in Firebase.
Firebase: How to display a thread of items in reverse order with a limit for each request and an indicator for a "load more" button.
This will get the last 10 items of the list
FBRef.child("childName")
.limitToLast(loadMoreLimit) // loadMoreLimit = 10 for example
This will get the last 10 items. Grab the id of the last record in the list and save for the load more functionality. Next, convert the collection of objects into and an array and do a list.reverse().
LOAD MORE Functionality: The next call will do two things, it will get the next sequence of list items based on the reference id from the first request and give you an indicator if you need to display the "load more" button.
this.FBRef
.child("childName")
.endAt(null, lastThreadId) // Get this from the previous step
.limitToLast(loadMoreLimit+2)
You will need to strip the first and last item of this object collection. The first item is the reference to get this list. The last item is an indicator for the show more button.
I have a bunch of other logic that will keep everything clean. You will need to add this code only for the load more functionality.
list = snapObjectAsArray; // The list is an array from snapObject
lastItemId = key; // get the first key of the list
if (list.length < loadMoreLimit+1) {
lastItemId = false;
}
if (list.length > loadMoreLimit+1) {
list.pop();
}
if (list.length > loadMoreLimit) {
list.shift();
}
// Return the list.reverse() and lastItemId
// If lastItemId is an ID, it will be used for the next reference and a flag to show the "load more" button.
}
I'm using ReactFire for easy Firebase integration.
Basically, it helps me storing the datas into the component state, as an array. Then, all I have to use is the reverse() function (read more)
Here is how I achieve this :
import React, { Component, PropTypes } from 'react';
import ReactMixin from 'react-mixin';
import ReactFireMixin from 'reactfire';
import Firebase from '../../../utils/firebaseUtils'; // Firebase.initializeApp(config);
#ReactMixin.decorate(ReactFireMixin)
export default class Add extends Component {
constructor(args) {
super(args);
this.state = {
articles: []
};
}
componentWillMount() {
let ref = Firebase.database().ref('articles').orderByChild('insertDate').limitToLast(10);
this.bindAsArray(ref, 'articles'); // bind retrieved data to this.state.articles
}
render() {
return (
<div>
{
this.state.articles.reverse().map(function(article) {
return <div>{article.title}</div>
})
}
</div>
);
}
}
There is a better way. You should order by negative server timestamp. How to get negative server timestamp even offline? There is an hidden field which helps. Related snippet from documentation:
var offsetRef = new Firebase("https://<YOUR-FIREBASE-APP>.firebaseio.com/.info/serverTimeOffset");
offsetRef.on("value", function(snap) {
var offset = snap.val();
var estimatedServerTimeMs = new Date().getTime() + offset;
});
To add to Dave Vávra's answer, I use a negative timestamp as my sort_key like so
Setting
const timestamp = new Date().getTime();
const data = {
name: 'John Doe',
city: 'New York',
sort_key: timestamp * -1 // Gets the negative value of the timestamp
}
Getting
const ref = firebase.database().ref('business-images').child(id);
const query = ref.orderByChild('sort_key');
return $firebaseArray(query); // AngularFire function
This fetches all objects from newest to oldest. You can also $indexOn the sortKey to make it run even faster
I had this problem too, I found a very simple solution to this that doesn't involved manipulating the data in anyway. If you are rending the result to the DOM, in a list of some sort. You can use flexbox and setup a class to reverse the elements in their container.
.reverse {
display: flex;
flex-direction: column-reverse;
}
myarray.reverse(); or this.myitems = items.map(item => item).reverse();
I did this by prepend.
query.orderByChild('sell').limitToLast(4).on("value", function(snapshot){
snapshot.forEach(function (childSnapshot) {
// PREPEND
});
});
Someone has pointed out that there are 2 ways to do this:
Manipulate the data client-side
Make a query that will order the data
The easiest way that I have found to do this is to use option 1, but through a LinkedList. I just append each of the objects to the front of the stack. It is flexible enough to still allow the list to be used in a ListView or RecyclerView. This way even though they come in order oldest to newest, you can still view, or retrieve, newest to oldest.
You can add a column named orderColumn where you save time as
Long refrenceTime = "large future time";
Long currentTime = "currentTime";
Long order = refrenceTime - currentTime;
now save Long order in column named orderColumn and when you retrieve data
as orderBy(orderColumn) you will get what you need.
just use reverse() on the array , suppose if you are storing the values to an array items[] then do a this.items.reverse()
ref.subscribe(snapshots => {
this.loading.dismiss();
this.items = [];
snapshots.forEach(snapshot => {
this.items.push(snapshot);
});
**this.items.reverse();**
},
For me it was limitToLast that worked. I also found out that limitLast is NOT a function:)
const query = messagesRef.orderBy('createdAt', 'asc').limitToLast(25);
The above is what worked for me.
PRINT in reverse order
Let's think outside the box... If your information will be printed directly into user's screen (without any content that needs to be modified in a consecutive order, like a sum or something), simply print from bottom to top.
So, instead of inserting each new block of content to the end of the print space (A += B), add that block to the beginning (A = B+A).
If you'll include the elements as a consecutive ordered list, the DOM can put the numbers for you if you insert each element as a List Item (<li>) inside an Ordered Lists (<ol>).
This way you save space from your database, avoiding unnecesary reversed data.

Observed Lists and Maps, and Firebase, oh my. How can I improve this mess?

So this is what I ended up with to get realtime starring/liking (of communities, in my case) working, with a Firebase datastore. It's a mess and surely I'm missing some fundamentals.
Here my element gets communities, each as a Map community stored in an observed List communities. It has to rewrite that List several times as it changes each community Map based on the results of the changed star count and the user's starred state, and some other fun:
getCommunities() {
// Since we call this method a second time after user
// signed in, clear the communities list before we recreate it.
if (communities.length > 0) { communities.clear(); }
var firebaseRoot = new db.Firebase(firebaseLocation);
var communityRef = firebaseRoot.child('/communities');
// TODO: Undo the limit of 20; https://github.com/firebase/firebase-dart/issues/8
communityRef.limit(20).onChildAdded.listen((e) {
var community = e.snapshot.val();
// snapshot.name is Firebase's ID, i.e. "the name of the Firebase location",
// so we'll add that to our local item list.
community['id'] = e.snapshot.name();
print(community['id']);
// If the user is signed in, see if they've starred this community.
if (app.user != null) {
firebaseRoot.child('/users/' + app.user.username + '/communities/' + community['id']).onValue.listen((e) {
if (e.snapshot.val() == null) {
community['userStarred'] = false;
// TODO: Add community star_count?!
} else {
community['userStarred'] = true;
}
print("${community['userStarred']}, star count: ${community['star_count']}");
// Replace the community in the observed list w/ our updated copy.
communities
..removeWhere((oldItem) => oldItem['alias'] == community['alias'])
..add(community)
..sort((m1, m2) => m1["updatedDate"].compareTo(m2["updatedDate"]));
communities = toObservable(communities.reversed.toList());
});
}
// If no updated date, use the created date.
if (community['updatedDate'] == null) {
community['updatedDate'] = community['createdDate'];
}
// Handle the case where no star count yet.
if (community['star_count'] == null) {
community['star_count'] = 0;
}
// The live-date-time element needs parsed dates.
community['updatedDate'] = DateTime.parse(community['updatedDate']);
community['createdDate'] = DateTime.parse(community['createdDate']);
// Listen for realtime changes to the star count.
communityRef.child(community['alias'] + '/star_count').onValue.listen((e) {
int newCount = e.snapshot.val();
community['star_count'] = newCount;
// Replace the community in the observed list w/ our updated copy.
// TODO: Re-writing the list each time is ridiculous!
communities
..removeWhere((oldItem) => oldItem['alias'] == community['alias'])
..add(community)
..sort((m1, m2) => m1["updatedDate"].compareTo(m2["updatedDate"]));
communities = toObservable(communities.reversed.toList());
});
// Insert each new community into the list.
communities.add(community);
// Sort the list by the item's updatedDate, then reverse it.
communities.sort((m1, m2) => m1["updatedDate"].compareTo(m2["updatedDate"]));
communities = toObservable(communities.reversed.toList());
});
}
Here we toggle the star, which again replaces the observed communities List a few times as we update the count in the affected community Maps and thus rewrite the List to reflect that:
toggleStar(Event e, var detail, Element target) {
// Don't fire the core-item's on-click, just the icon's.
e.stopPropagation();
if (app.user == null) {
app.showMessage("Kindly sign in first.", "important");
return;
}
bool isStarred = (target.classes.contains("selected"));
var community = communities.firstWhere((i) => i['id'] == target.dataset['id']);
var firebaseRoot = new db.Firebase(firebaseLocation);
var starredCommunityRef = firebaseRoot.child('/users/' + app.user.username + '/communities/' + community['id']);
var communityRef = firebaseRoot.child('/communities/' + community['id']);
if (isStarred) {
// If it's starred, time to unstar it.
community['userStarred'] = false;
starredCommunityRef.remove();
// Update the star count.
communityRef.child('/star_count').transaction((currentCount) {
if (currentCount == null || currentCount == 0) {
community['star_count'] = 0;
return 0;
} else {
community['star_count'] = currentCount - 1;
return currentCount - 1;
}
});
// Update the list of users who starred.
communityRef.child('/star_users/' + app.user.username).remove();
} else {
// If it's not starred, time to star it.
community['userStarred'] = true;
starredCommunityRef.set(true);
// Update the star count.
communityRef.child('/star_count').transaction((currentCount) {
if (currentCount == null || currentCount == 0) {
community['star_count'] = 1;
return 1;
} else {
community['star_count'] = currentCount + 1;
return currentCount + 1;
}
});
// Update the list of users who starred.
communityRef.child('/star_users/' + app.user.username).set(true);
}
// Replace the community in the observed list w/ our updated copy.
communities.removeWhere((oldItem) => oldItem['alias'] == community['alias']);
communities.add(community);
communities.sort((m1, m2) => m1["updatedDate"].compareTo(m2["updatedDate"]));
communities = toObservable(communities.reversed.toList());
print(communities);
}
There's also some other craziness where we have to get the list of communities again when app.changes because we only load app.user after the app and list initially load, and now that we have the user we need to turn on the appropriate stars. So my attached() looks like:
attached() {
app.pageTitle = "Communities";
getCommunities();
app.changes.listen((List<ChangeRecord> records) {
if (app.user != null) {
getCommunities();
}
});
}
There, it seems I could just be getting the stars and updating said each affected community Map, then repopulating the observed communities List, but that's the least of it.
The full thing: https://gist.github.com/DaveNotik/5ccdc9e74429cf87d641
How can I improve all this Map/List management, e.g. where every time I change a community Map, I have to rewrite the whole communities List? Should I be thinking of it differently?
What about all this querying Firebase? Surely, there's a better way, but it seems I need to do a lot to keep it realtime, and also the element gets attached and detached, so it seems I need to run getCommunities() each time. Unless the OOP way is objects get created, and they're always there to be observed whenever the element is attached? I'm missing those fundamentals.
This app.changes business to handle the case where we load the list before we have the app.user (which then means we want to load her stars) - is there a better way?
Other ridiculousness?
Big question, I know. Thank you for helping me get a handle on the right approach as I move forward!
I think there is two different ways to choose, if you want to keep a data of your application in real time sync with server database:
1 Polling (pull method ie. a client pulls the data from server)
Application polls ie. requests the updated data from the server. Polling can be automatic (for example with interval of 60s) or requested by user (= refresh). The short automatic interval will cause high load on server and with long interval you lose real time feeling.
2 Full-duplex (push method ie. server can push the data to the client)
An application and a server have full-duplex connection in between and server is able to send the data or a notification of the data available to the client. Then the client can decide whether or not to retrieve the data.
This method is a modern one, because it'll keep the net traffic and the server load in minimum and yet providing a real time updates.
The firebase boasts with this kind of updates, but I'm not sure is it full-dublex or just a clever way of polling. Websocket protocol is a real full-duplex connection and dart server supports it.
The updated data from a server can include:
1 A full dataset
Basically the server sends a full dataset (=initial query) and the server doesn't "know" anything about updated data. This is easiest way to go, if you have reasonable small datasets. Many times you'll have a very small datasets among the big ones, so this way can be useful.
2 A dataset including a new data only
The server can send a dataset based on modified timestamp ie. every time a record in the database changes, a timestamp for update will be saved and the query can be filtered based on this timestamp. In other words application knows when it has last updated the data and then requests newer data.
3 A changed record
A server keeps a track of updated data and sends it to the application. The data can be sent record by record when changes occurs or server can collect the data for a bigger chunks to be sent. This method requires a server to keep a track of every client connected in order to send a correct data to each client. When you add an authentication process for clients ie. not every data can be send to all, it can get quite complicated.
I think the easiest way is to use the method number 2 for updated data.
Last thing...
What to do with the data received?
1 Handle everything as a new
If application receives an updated data, it will destroy/clear all the lists and maps and recreate/refill them with the new data. Typical problems with this are a user loses a current position on a page or the data user were looking jumps around. If application has modified or extended an old data for some reason, all those modifications will be lost. This method works ok, if a user requests a refresh.
2 Update only the changed data
The application never clears initial list or maps, it just updates them with a new received data. Typically you will construct a new combined map from queried data for your specific need (for example a certain view). The combined map has already all information you want to show in the specific view (default values even if the initial queries didn't had the data for the field) and you just update a new values in it.
If the updated information needs a new member in the list you just add it in the end.
If the updated information requires a deletion from the list, it might be a good thing to use extra field "active" and filter the list/map with it. With filtering you won't lose any referencies or so.
If you need to sort a data or filter it, it should be done by a view or user request. Basically the data is stored in the application and updated as needed. When a user needs to see the data in a specific way, the view should show the data a proper way. This is called model-controller-view and the main idea is to separate the data from the view.
I'm sorry this long answer didn't answer any of your questions, but I tried to cut this challenge to a smaller chunks. Many times you can see an interface between these chunks and you can design and organize your code nicely by using these interfaces.

How to implement pagination when using amazon Dynamo DB in rails

I want to use amazon Dynamo DB with rails.But I have not found a way to implement pagination.
I will use AWS::Record::HashModel as ORM.
This ORM supports limits like this:
People.limit(10).each {|person| ... }
But I could not figured out how to implement following MySql query in Dynamo DB.
SELECT *
FROM `People`
LIMIT 1 , 30
You issue queries using LIMIT. If the subset returned does not contain the full table, a LastEvaluatedKey value is returned. You use this value as the ExclusiveStartKey in the next query. And so on...
From the DynamoDB Developer Guide.
You can provide 'page-size' in you query to set the result set size.
The response of DynamoDB contains 'LastEvaluatedKey' which will indicate the last key as per the page size. If response does't contain 'LastEvaluatedKey' it means there are no results left to fetch.
Use the 'LastEvaluatedKey' as 'ExclusiveStartKey' while fetching next time.
I hope this helps.
DynamoDB Pagination
Here's a simple copy-paste-run proof of concept (Node.js) for stateless forward/reverse navigation with dynamodb. In summary; each response includes the navigation history, allowing user to explicitly and consistently request either the next or previous page (while next/prev params exist):
GET /accounts -> first page
GET /accounts?next=A3r0ijKJ8 -> next page
GET /accounts?prev=R4tY69kUI -> previous page
Considerations:
If your ids are large and/or users might do a lot of navigation, then the potential size of the next/prev params might become too large.
Yes you do have to store the entire reverse path - if you only store the previous page marker (per some other answers) you will only be able to go back one page.
It won't handle changing pageSize midway, consider baking pageSize into the next/prev value.
base64 encode the next/prev values, and you could also encrypt.
Scans are inefficient, while this suited my current requirement it won't suit all!
// demo.js
const mockTable = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]
const getPagedItems = (pageSize = 5, cursor = {}) => {
// Parse cursor
const keys = cursor.next || cursor.prev || [] // fwd first
let key = keys[keys.length-1] || null // eg ddb's PK
// Mock query (mimic dynamodb response)
const Items = mockTable.slice(parseInt(key) || 0, pageSize+key)
const LastEvaluatedKey = Items[Items.length-1] < mockTable.length
? Items[Items.length-1] : null
// Build response
const res = {items:Items}
if (keys.length > 0) // add reverse nav keys (if any)
res.prev = keys.slice(0, keys.length-1)
if (LastEvaluatedKey) // add forward nav keys (if any)
res.next = [...keys, LastEvaluatedKey]
return res
}
// Run test ------------------------------------
const runTest = () => {
const PAGE_SIZE = 6
let x = {}, i = 0
// Page to end
while (i == 0 || x.next) {
x = getPagedItems(PAGE_SIZE, {next:x.next})
console.log(`Page ${++i}: `, x.items)
}
// Page back to start
while (x.prev) {
x = getPagedItems(PAGE_SIZE, {prev:x.prev})
console.log(`Page ${--i}: `, x.items)
}
}
runTest()
I faced a similar problem.
The generic pagination approach is, use "start index" or "start page" and the "page length". 
The "ExclusiveStartKey" and "LastEvaluatedKey" based approach is very DynamoDB specific.
I feel this DynamoDB specific implementation of pagination should be hidden from the API client/UI.
Also in case, the application is serverless, using service like Lambda, it will be not be possible to maintain the state on the server. The other side is the client implementation will become very complex.
I came with a different approach, which I think is generic ( and not specific to DynamoDB)
When the API client specifies the start index, fetch all the keys from
the table and store it into an array.
Find out the key for the start index from the array, which is
specified by the client.
Make use of the ExclusiveStartKey and fetch the number of records, as
specified in the page length.
If the start index parameter is not present, the above steps are not
needed, we don't need to specify the ExclusiveStartKey in the scan
operation.
This solution has some drawbacks -
We will need to fetch all the keys when the user needs pagination with
start index.
We will need additional memory to store the Ids and the indexes.
Additional database scan operations ( one or multiple to fetch the
keys )
But I feel this will be very easy approach for the clients, which are using our APIs. The backward scan will work seamlessly. If the user wants to see "nth" page, this will be possible.
In fact I faced the same problem and I noticed that LastEvaluatedKey and ExclusiveStartKey are not working well especially when using Scan So I solved Like this.
GET/?page_no=1&page_size=10 =====> first page
response will contain count of records and first 10 records
retry and increase number of page until all record come.
Code is below
PS: I am using python
first_index = ((page_no-1)*page_size)
second_index = (page_no*page_size)
if (second_index > len(response['Items'])):
second_index = len(response['Items'])
return {
'statusCode': 200,
'count': response['Count'],
'response': response['Items'][first_index:second_index]
}

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