neo4j cypher - how to find all nodes that have a relationship to list of nodes - neo4j

I have nodes- named "options". "Users" choose these options. I need a chpher query that works like this:
retrieve users who had chosen all the options those are given as a list.
MATCH (option:Option)<-[:CHOSE]-(user:User) WHERE option.Key IN ['1','2','2'] Return user
This query gives me users who chose option(1), option(2) and option(3) and also gives me the user who only chose option(2).
What I need is only the users who chose all of them -option(1), option(2) and option(3).

For an all cypher solution (don't know if it's better than Chris' answer, you'll have to test and compare) you can collect the option.Key for each user and filter out those who don't have a option.Key for each value in your list
MATCH (u:User)-[:CHOSE]->(opt:Option)
WITH u, collect(opt.Key) as optKeys
WHERE ALL (v IN {values} WHERE v IN optKeys)
RETURN u
or match all the options whose keys are in your list and the users that chose them, collect those options per user and compare the size of the option collection to the size of your list (if you don't give duplicates in your list the user with an option collection of equal size has chosen all the options)
MATCH (u:User)-[:CHOSE]->(opt:Option)
WHERE opt.Key IN {values}
WITH u, collect(opt) as opts
WHERE length(opts) = length({values}) // assuming {values} don't have duplicates
RETURN u
Either should limit results to users connected with all the options whose key values are specified in {values} and you can vary the length of the collection parameter without changing the query.

If the number of options is limited, you could do:
MATCH
(user:User)-[:Chose]->(option1:Option),
(user)-[:Chose]->(option2:Option),
(user)-[:Chose]->(option3:Option)
WHERE
option1.Key = '1'
AND option2.Key = '2'
AND option3.Key = '3'
RETURN
user.Id
Which will only return the user with all 3 options.
It's a bit rubbishy as obviously you end up with 3 lines where you have 1, but I don't know how to do what you want using the IN keyword.
If you're coding against it, it's pretty simple to generate the WHERE and MATCH clause, but still - not ideal. :(
EDIT - Example
Turns out there is some string manipulation going on here (!), but you can always cache bits. Importantly - it's using Params which would allow neo4j to cache the queries and supply faster responses with each call.
public static IEnumerable<User> GetUser(IGraphClient gc)
{
var query = GenerateCypher(gc, new[] {"1", "2", "3"});
return query.Return(user => user.As<User>()).Results;
}
public static ICypherFluentQuery GenerateCypher(IGraphClient gc, string[] options)
{
ICypherFluentQuery query = new CypherFluentQuery(gc);
for(int i = 0; i < options.Length; i++)
query = query.Match(string.Format("(user:User)-[:CHOSE]->(option{0}:Option)", i));
for (int i = 0; i < options.Length; i++)
{
string paramName = string.Format("option{0}param", i);
string whereString = string.Format("option{0}.Key = {{{1}}}", i, paramName);
query = i == 0 ? query.Where(whereString) : query.AndWhere(whereString);
query = query.WithParam(paramName, options[i]);
}
return query;
}

MATCH (user:User)-[:CHOSE]->(option:Option)
WHERE option.key IN ['1', '2', '3']
WITH user, COUNT(*) AS num_options_chosen
WHERE num_options_chosen = LENGTH(['1', '2', '3'])
RETURN user.name
This will only return users that have relationships with all the Options with the given keys in the array. This assumes there are not multiple [:CHOSE] relationships between users and options. If it is possible for a user to have multiple [:CHOSE] relationships with a single option, you'll have to add some conditionals as necessary.
I tested the above query with the below dataset:
CREATE (User1:User {name:'User 1'}),
(User2:User {name:'User 2'}),
(User3:User {name:'User 3'}),
(Option1:Option {key:'1'}),
(Option2:Option {key:'2'}),
(Option3:Option {key:'3'}),
(Option4:Option {key:'4'}),
(User1)-[:CHOSE]->(Option1),
(User1)-[:CHOSE]->(Option4),
(User2)-[:CHOSE]->(Option2),
(User2)-[:CHOSE]->(Option3),
(User3)-[:CHOSE]->(Option1),
(User3)-[:CHOSE]->(Option2),
(User3)-[:CHOSE]->(Option3),
(User3)-[:CHOSE]->(Option4)
And I get only 'User 3' as the output.

For shorter lists, you can use path predicates in your WHERE clause:
MATCH (user:User)
WHERE (user)-[:CHOSE]->(:Option { Key: '1' })
AND (user)-[:CHOSE]->(:Option { Key: '2' })
AND (user)-[:CHOSE]->(:Option { Key: '3' })
RETURN user
Advantages:
Clear to read
Easy to generate for dynamic length lists
Disadvantages:
For each different length, you will have a different query that has to be parsed and cached by Cypher. Too many dynamic queries will watch your cache hit rate go through the floor, query compilation work go up, and query performance go down.

Related

Grails distinct projection get the result count of distinct items

I am using grails-2.5.6 version. I am using spring-security-core plugin. I have a criteria query on UserRole table. Where I want to find all distinct users by a role. It is working properly.
But the problem is the pagination effect. When I am counting on the list it is counting on UserRole list object. But I need the count on distinct projection items. Here is my attempt below:
def list(Integer max) {
def userInstanceList = UserRole.createCriteria().list(params) {
createAlias('user', 'au')
createAlias('role', 'ar')
projections {
distinct("user")
}
if (params.roleId) {
eq('ar.id', params.getLong("roleId"))
}
}
def totalCount = userInstanceList.totalCount
[userInstanceList: userInstanceList, totalCount: totalCount]
}
Here, totalCount is the number of UserRole list. But I want the distinct projection count.
I would tackle this slightly differently, you want to analyse the users, not the userroles.
So I'd do something like:
List<User> usersWithRole = UserRole.createCriteria().list(params) {
role {
eq('id', params.getLong("roleId"))
}
}*.user
int count = usersWithRole.size()
Unless of course there's hundreds or thousands of users, in which case I wouldn't want to load all of them each time and would revert to SQL.
Is this a custom version of spring security you're using? I've never seen Roles with a 'long' based ID, usually, the key is a String representing the Authority name.
Usually the DBAs see the use of distinct keyword as a code-smell.
In your case I would rather use the User as the main domain object to run the query against and a group by clause:
long id = params.getLong "roleId"
def list = User.createCriteria().list( params ) {
projections{
groupProperty 'userRole.role.id'
}
if( id )
userRole{
role{
eq 'id', id
}
}
}

How to get random data from firestore? [duplicate]

It is crucial for my application to be able to select multiple documents at random from a collection in firebase.
Since there is no native function built in to Firebase (that I know of) to achieve a query that does just this, my first thought was to use query cursors to select a random start and end index provided that I have the number of documents in the collection.
This approach would work but only in a limited fashion since every document would be served up in sequence with its neighboring documents every time; however, if I was able to select a document by its index in its parent collection I could achieve a random document query but the problem is I can't find any documentation that describes how you can do this or even if you can do this.
Here's what I'd like to be able to do, consider the following firestore schema:
root/
posts/
docA
docB
docC
docD
Then in my client (I'm in a Swift environment) I'd like to write a query that can do this:
db.collection("posts")[0, 1, 3] // would return: docA, docB, docD
Is there anyway I can do something along the lines of this? Or, is there a different way I can select random documents in a similar fashion?
Please help.
Using randomly generated indexes and simple queries, you can randomly select documents from a collection or collection group in Cloud Firestore.
This answer is broken into 4 sections with different options in each section:
How to generate the random indexes
How to query the random indexes
Selecting multiple random documents
Reseeding for ongoing randomness
How to generate the random indexes
The basis of this answer is creating an indexed field that when ordered ascending or descending, results in all the document being randomly ordered. There are different ways to create this, so let's look at 2, starting with the most readily available.
Auto-Id version
If you are using the randomly generated automatic ids provided in our client libraries, you can use this same system to randomly select a document. In this case, the randomly ordered index is the document id.
Later in our query section, the random value you generate is a new auto-id (iOS, Android, Web) and the field you query is the __name__ field, and the 'low value' mentioned later is an empty string. This is by far the easiest method to generate the random index and works regardless of the language and platform.
By default, the document name (__name__) is only indexed ascending, and you also cannot rename an existing document short of deleting and recreating. If you need either of these, you can still use this method and just store an auto-id as an actual field called random rather than overloading the document name for this purpose.
Random Integer version
When you write a document, first generate a random integer in a bounded range and set it as a field called random. Depending on the number of documents you expect, you can use a different bounded range to save space or reduce the risk of collisions (which reduce the effectiveness of this technique).
You should consider which languages you need as there will be different considerations. While Swift is easy, JavaScript notably can have a gotcha:
32-bit integer: Great for small (~10K unlikely to have a collision) datasets
64-bit integer: Large datasets (note: JavaScript doesn't natively support, yet)
This will create an index with your documents randomly sorted. Later in our query section, the random value you generate will be another one of these values, and the 'low value' mentioned later will be -1.
How to query the random indexes
Now that you have a random index, you'll want to query it. Below we look at some simple variants to select a 1 random document, as well as options to select more than 1.
For all these options, you'll want to generate a new random value in the same form as the indexed values you created when writing the document, denoted by the variable random below. We'll use this value to find a random spot on the index.
Wrap-around
Now that you have a random value, you can query for a single document:
let postsRef = db.collection("posts")
queryRef = postsRef.whereField("random", isGreaterThanOrEqualTo: random)
.order(by: "random")
.limit(to: 1)
Check that this has returned a document. If it doesn't, query again but use the 'low value' for your random index. For example, if you did Random Integers then lowValue is 0:
let postsRef = db.collection("posts")
queryRef = postsRef.whereField("random", isGreaterThanOrEqualTo: lowValue)
.order(by: "random")
.limit(to: 1)
As long as you have a single document, you'll be guaranteed to return at least 1 document.
Bi-directional
The wrap-around method is simple to implement and allows you to optimize storage with only an ascending index enabled. One downside is the possibility of values being unfairly shielded. E.g if the first 3 documents (A,B,C) out of 10K have random index values of A:409496, B:436496, C:818992, then A and C have just less than 1/10K chance of being selected, whereas B is effectively shielded by the proximity of A and only roughly a 1/160K chance.
Rather than querying in a single direction and wrapping around if a value is not found, you can instead randomly select between >= and <=, which reduces the probability of unfairly shielded values by half, at the cost of double the index storage.
If one direction returns no results, switch to the other direction:
queryRef = postsRef.whereField("random", isLessThanOrEqualTo: random)
.order(by: "random", descending: true)
.limit(to: 1)
queryRef = postsRef.whereField("random", isGreaterThanOrEqualTo: random)
.order(by: "random")
.limit(to: 1)
Selecting multiple random documents
Often, you'll want to select more than 1 random document at a time. There are 2 different ways to adjust the above techniques depending on what trade offs you want.
Rinse & Repeat
This method is straight forward. Simply repeat the process, including selecting a new random integer each time.
This method will give you random sequences of documents without worrying about seeing the same patterns repeatedly.
The trade-off is it will be slower than the next method since it requires a separate round trip to the service for each document.
Keep it coming
In this approach, simply increase the number in the limit to the desired documents. It's a little more complex as you might return 0..limit documents in the call. You'll then need to get the missing documents in the same manner, but with the limit reduced to only the difference. If you know there are more documents in total than the number you are asking for, you can optimize by ignoring the edge case of never getting back enough documents on the second call (but not the first).
The trade-off with this solution is in repeated sequences. While the documents are randomly ordered, if you ever end up overlapping ranges you'll see the same pattern you saw before. There are ways to mitigate this concern discussed in the next section on reseeding.
This approach is faster than 'Rinse & Repeat' as you'll be requesting all the documents in the best case a single call or worst case 2 calls.
Reseeding for ongoing randomness
While this method gives you documents randomly if the document set is static the probability of each document being returned will be static as well. This is a problem as some values might have unfairly low or high probabilities based on the initial random values they got. In many use cases, this is fine but in some, you may want to increase the long term randomness to have a more uniform chance of returning any 1 document.
Note that inserted documents will end up weaved in-between, gradually changing the probabilities, as will deleting documents. If the insert/delete rate is too small given the number of documents, there are a few strategies addressing this.
Multi-Random
Rather than worrying out reseeding, you can always create multiple random indexes per document, then randomly select one of those indexes each time. For example, have the field random be a map with subfields 1 to 3:
{'random': {'1': 32456, '2':3904515723, '3': 766958445}}
Now you'll be querying against random.1, random.2, random.3 randomly, creating a greater spread of randomness. This essentially trades increased storage to save increased compute (document writes) of having to reseed.
Reseed on writes
Any time you update a document, re-generate the random value(s) of the random field. This will move the document around in the random index.
Reseed on reads
If the random values generated are not uniformly distributed (they're random, so this is expected), then the same document might be picked a dispropriate amount of the time. This is easily counteracted by updating the randomly selected document with new random values after it is read.
Since writes are more expensive and can hotspot, you can elect to only update on read a subset of the time (e.g, if random(0,100) === 0) update;).
Posting this to help anyone that has this problem in the future.
If you are using Auto IDs you can generate a new Auto ID and query for the closest Auto ID as mentioned in Dan McGrath's Answer.
I recently created a random quote api and needed to get random quotes from a firestore collection.
This is how I solved that problem:
var db = admin.firestore();
var quotes = db.collection("quotes");
var key = quotes.doc().id;
quotes.where(admin.firestore.FieldPath.documentId(), '>=', key).limit(1).get()
.then(snapshot => {
if(snapshot.size > 0) {
snapshot.forEach(doc => {
console.log(doc.id, '=>', doc.data());
});
}
else {
var quote = quotes.where(admin.firestore.FieldPath.documentId(), '<', key).limit(1).get()
.then(snapshot => {
snapshot.forEach(doc => {
console.log(doc.id, '=>', doc.data());
});
})
.catch(err => {
console.log('Error getting documents', err);
});
}
})
.catch(err => {
console.log('Error getting documents', err);
});
The key to the query is this:
.where(admin.firestore.FieldPath.documentId(), '>', key)
And calling it again with the operation reversed if no documents are found.
I hope this helps!
Just made this work in Angular 7 + RxJS, so sharing here with people who want an example.
I used #Dan McGrath 's answer, and I chose these options: Random Integer version + Rinse & Repeat for multiple numbers. I also used the stuff explained in this article: RxJS, where is the If-Else Operator? to make if/else statements on stream level (just if any of you need a primer on that).
Also note I used angularfire2 for easy Firebase integration in Angular.
Here is the code:
import { Component, OnInit } from '#angular/core';
import { Observable, merge, pipe } from 'rxjs';
import { map, switchMap, filter, take } from 'rxjs/operators';
import { AngularFirestore, QuerySnapshot } from '#angular/fire/firestore';
#Component({
selector: 'pp-random',
templateUrl: './random.component.html',
styleUrls: ['./random.component.scss']
})
export class RandomComponent implements OnInit {
constructor(
public afs: AngularFirestore,
) { }
ngOnInit() {
}
public buttonClicked(): void {
this.getRandom().pipe(take(1)).subscribe();
}
public getRandom(): Observable<any[]> {
const randomNumber = this.getRandomNumber();
const request$ = this.afs.collection('your-collection', ref => ref.where('random', '>=', randomNumber).orderBy('random').limit(1)).get();
const retryRequest$ = this.afs.collection('your-collection', ref => ref.where('random', '<=', randomNumber).orderBy('random', 'desc').limit(1)).get();
const docMap = pipe(
map((docs: QuerySnapshot<any>) => {
return docs.docs.map(e => {
return {
id: e.id,
...e.data()
} as any;
});
})
);
const random$ = request$.pipe(docMap).pipe(filter(x => x !== undefined && x[0] !== undefined));
const retry$ = request$.pipe(docMap).pipe(
filter(x => x === undefined || x[0] === undefined),
switchMap(() => retryRequest$),
docMap
);
return merge(random$, retry$);
}
public getRandomNumber(): number {
const min = Math.ceil(Number.MIN_VALUE);
const max = Math.ceil(Number.MAX_VALUE);
return Math.floor(Math.random() * (max - min + 1)) + min;
}
}
The other solutions are better but seems hard for me to understand, so I came up with another method
Use incremental number as ID like 1,2,3,4,5,6,7,8,9, watch out for delete documents else we
have an I'd that is missing
Get total number of documents in the collection, something like this, I don't know of a better solution than this
let totalDoc = db.collection("stat").get().then(snap=>snap.size)
Now that we have these, create an empty array to store random list of number, let's say we want 20 random documents.
let randomID = [ ]
while(randomID.length < 20) {
const randNo = Math.floor(Math.random() * totalDoc) + 1;
if(randomID.indexOf(randNo) === -1) randomID.push(randNo);
}
now we have our 20 random documents id
finally we fetch our data from fire store, and save to randomDocs array by mapping through the randomID array
const randomDocs = randomID.map(id => {
db.collection("posts").doc(id).get()
.then(doc => {
if (doc.exists) return doc.data()
})
.catch(error => {
console.log("Error getting document:", error);
});
})
I'm new to firebase, but I think with this answers we can get something better or a built-in query from firebase soon
After intense argument with my friend, we finally found some solution
If you don't need to set document's id to be RandomID, just name documents as size of collection's size.
For example, first document of collection is named '0'.
second document name should be '1'.
Then, we just read the size of collection, for example N, and we can get random number A in range of [0~N).
And then, we can query the document named A.
This way can give same probability of randomness to every documents in collection.
undoubtedly Above accepted Answer is SuperUseful but There is one case like If we had a collection of some Documents(about 100-1000) and we want some 20-30 random Documents Provided that Document must not be repeated. (case In Random Problems App etc...).
Problem with the Above Solution:
For a small number of documents in the Collection(say 50) Probability of repetition is high. To avoid it If I store Fetched Docs Id and Add-in Query like this:
queryRef = postsRef.whereField("random", isGreaterThanOrEqualTo: lowValue).where("__name__", isNotEqualTo:"PreviousId")
.order(by: "random")
.limit(to: 1)
here PreviousId is Id of all Elements that were fetched Already means A loop of n previous Ids.
But in this case, network Call would be high.
My Solution:
Maintain one Special Document and Keep a Record of Ids of this Collection only, and fetched this document First Time and Then Do all Randomness Stuff and check for previously not fetched on App site. So in this case network call would be only the same as the number of documents requires (n+1).
Disadvantage of My solution:
Have to maintain A document so Write on Addition and Deletion. But it is good If reads are very often then Writes which occurs in most cases.
You can use listDocuments() property for get only Query list of documents id. Then generate random id using the following way and get DocumentSnapshot with get() property.
var restaurantQueryReference = admin.firestore().collection("Restaurant"); //have +500 docs
var restaurantQueryList = await restaurantQueryReference.listDocuments(); //get all docs id;
for (var i = restaurantQueryList.length - 1; i > 0; i--) {
var j = Math.floor(Math.random() * (i + 1));
var temp = restaurantQueryList[i];
restaurantQueryList[i] = restaurantQueryList[j];
restaurantQueryList[j] = temp;
}
var restaurantId = restaurantQueryList[Math.floor(Math.random()*restaurantQueryList.length)].id; //this is random documentId
Unlike rtdb, firestore ids are not ordered chronologically. So using Auto-Id version described by Dan McGrath is easily implemented if you use the auto-generated id by the firestore client.
new Promise<Timeline | undefined>(async (resolve, reject) => {
try {
let randomTimeline: Timeline | undefined;
let maxCounter = 5;
do {
const randomId = this.afs.createId(); // AngularFirestore
const direction = getRandomIntInclusive(1, 10) <= 5;
// The firestore id is saved with your model as an "id" property.
let list = await this.list(ref => ref
.where('id', direction ? '>=' : '<=', randomId)
.orderBy('id', direction ? 'asc' : 'desc')
.limit(10)
).pipe(take(1)).toPromise();
// app specific filtering
list = list.filter(x => notThisId !== x.id && x.mediaCounter > 5);
if (list.length) {
randomTimeline = list[getRandomIntInclusive(0, list.length - 1)];
}
} while (!randomTimeline && maxCounter-- >= 0);
resolve(randomTimeline);
} catch (err) {
reject(err);
}
})
I have one way to get random a list document in Firebase Firestore, it really easy. When i upload data on Firestore i creat a field name "position" with random value from 1 to 1 milions. When i get data from Fire store i will set Order by field "Position" and update value for it, a lot of user load data and data always update and it's will be random value.
For those using Angular + Firestore, building on #Dan McGrath techniques, here is the code snippet.
Below code snippet returns 1 document.
getDocumentRandomlyParent(): Observable<any> {
return this.getDocumentRandomlyChild()
.pipe(
expand((document: any) => document === null ? this.getDocumentRandomlyChild() : EMPTY),
);
}
getDocumentRandomlyChild(): Observable<any> {
const random = this.afs.createId();
return this.afs
.collection('my_collection', ref =>
ref
.where('random_identifier', '>', random)
.limit(1))
.valueChanges()
.pipe(
map((documentArray: any[]) => {
if (documentArray && documentArray.length) {
return documentArray[0];
} else {
return null;
}
}),
);
}
1) .expand() is a rxjs operation for recursion to ensure we definitely get a document from the random selection.
2) For recursion to work as expected we need to have 2 separate functions.
3) We use EMPTY to terminate .expand() operator.
import { Observable, EMPTY } from 'rxjs';
Ok I will post answer to this question even thou I am doing this for Android. Whenever i create a new document i initiate random number and set it to random field, so my document looks like
"field1" : "value1"
"field2" : "value2"
...
"random" : 13442 //this is the random number i generated upon creating document
When I query for random document I generate random number in same range that I used when creating document.
private val firestore: FirebaseFirestore = FirebaseFirestore.getInstance()
private var usersReference = firestore.collection("users")
val rnds = (0..20001).random()
usersReference.whereGreaterThanOrEqualTo("random",rnds).limit(1).get().addOnSuccessListener {
if (it.size() > 0) {
for (doc in it) {
Log.d("found", doc.toString())
}
} else {
usersReference.whereLessThan("random", rnds).limit(1).get().addOnSuccessListener {
for (doc in it) {
Log.d("found", doc.toString())
}
}
}
}
Based on #ajzbc answer I wrote this for Unity3D and its working for me.
FirebaseFirestore db;
void Start()
{
db = FirebaseFirestore.DefaultInstance;
}
public void GetRandomDocument()
{
Query query1 = db.Collection("Sports").WhereGreaterThanOrEqualTo(FieldPath.DocumentId, db.Collection("Sports").Document().Id).Limit(1);
Query query2 = db.Collection("Sports").WhereLessThan(FieldPath.DocumentId, db.Collection("Sports").Document().Id).Limit(1);
query1.GetSnapshotAsync().ContinueWithOnMainThread((querySnapshotTask1) =>
{
if(querySnapshotTask1.Result.Count > 0)
{
foreach (DocumentSnapshot documentSnapshot in querySnapshotTask1.Result.Documents)
{
Debug.Log("Random ID: "+documentSnapshot.Id);
}
} else
{
query2.GetSnapshotAsync().ContinueWithOnMainThread((querySnapshotTask2) =>
{
foreach (DocumentSnapshot documentSnapshot in querySnapshotTask2.Result.Documents)
{
Debug.Log("Random ID: " + documentSnapshot.Id);
}
});
}
});
}
If you are using autoID this may also work for you...
let collectionRef = admin.firestore().collection('your-collection');
const documentSnapshotArray = await collectionRef.get();
const records = documentSnapshotArray.docs;
const index = documentSnapshotArray.size;
let result = '';
console.log(`TOTAL SIZE=====${index}`);
var randomDocId = Math.floor(Math.random() * index);
const docRef = records[randomDocId].ref;
result = records[randomDocId].data();
console.log('----------- Random Result --------------------');
console.log(result);
console.log('----------- Random Result --------------------');
Easy (2022). You need something like:
export const getAtRandom = async (me) => {
const collection = admin.firestore().collection('...').where(...);
const { count } = (await collection.count().get()).data();
const numberAtRandom = Math.floor(Math.random() * count);
const snap = await accountCollection.limit(1).offset(numberAtRandom).get()
if (accountSnap.empty) return null;
const doc = { id: snap.docs[0].id, ...snap.docs[0].data(), ref: snap.docs[0].ref };
return doc;
}
The next code (Flutter) will return one or up to ten random documents from a Firebase collection.
None of the documents will be repeated
Max 10 documents can be retrieved
If you pass a greater numberOfDocuments than existing documents in the collection, the loop will never end.
Future<Iterable<QueryDocumentSnapshot>> getRandomDocuments(int numberOfDocuments) async {
// Queried documents
final docs = <QueryDocumentSnapshot>[];
// Queried documents id's. We will use later to avoid querying same documents
final currentIds = <String>[];
do {
// Generate random id explained by #Dan McGrath's answer (autoId)
final randomId = FirebaseFirestore.instance.collection('random').doc().id;
var query = FirebaseFirestore.instance
.collection('myCollection') // Change this for you collection name
.where(FieldPath.documentId, isGreaterThanOrEqualTo: randomId)
.limit(1);
if (currentIds.isNotEmpty) {
// If previously we fetched a document we avoid fetching the same
query = query.where(FieldPath.documentId, whereNotIn: currentIds);
}
final querySnap = await query.get();
for (var element in querySnap.docs) {
currentIds.add(element.id);
docs.add(element);
}
} while (docs.length < numberOfDocuments); // <- Run until we have all documents we want
return docs;
}

Grails: how to get last inserted record matching query

Getting the last record is trivial in SQL, e.g. (for MySQL)
class ExchangeRate {
Currency from
Currency to
BigDecimal rate // e.g. 10
Date dateCreated
}
class Currency {
String iso
etc..
}
SQL to get the latest is trivial:
Select max(id), rate
from exchange_rate
where from_id = 1
and to_id = 3
or
select rate
from exchange_rate
where from_id = 2
order by id desc
limit 1
The question is, how does one do this efficiently in Grails? I only want a single result.
This obviously wont work:
def query = ExchangeRate.where {
from == from && to == to && id == max(id)
}
ExchangeRate exchangeRate = query.find()
There have been several posts on this, but not with an actual answer which I could figure out how to apply (I am a SQL guy, and don't know hibernate language and would prefer a solution which did not involve it if there was one)
If there was an easy way to run SQL directly without having to hand manage result sets that would work (as we will never use another DB other than MySQL)
I am sure it could be done with sort and limit, but a) haven't found an example I could copy, and b) would assume this be inefficient, because it appears that the sorting and limiting is done in code, not SQL?
This example is in the documentation:
Book.findAll("from Book as b where b.author=:author",
[author: 'Dan Brown'], [max: 10, offset: 5])
could lead to this:
def exchangeRates = ExchangeRate.findAll("from ExchangeRate as e where e.from = :from order by id desc", [from: from], [max: 1])
if (exchangeRates.size() == 1) {
return exchangeRates.first().rate
}
return null
is there a better way (e.g. one which doesnt use hibernate low level language, or one which uses SQL instead, or one which is more efficient?)
Try using a subquery according to the documentation.
def query = ExchangeRate.where {
id = max(id).of { from == fromValue } && to == toValue
}
query.find()

LINQ query with omitted user input

so I have a form with several fields which are criteria for searching in a database.
I want to formulate a query using LINQ like so:
var Coll = (from obj in table where value1 = criteria1 && value2 = criteria2...)
and so on.
My problem is, I don't want to write it using If statements to check if every field has been filled in, nor do I want to make separate methods for the various search cases (criteria 1 and criteria 5 input; criteria 2 and criteria 3 input ... etc.)
So my question is: How can I achieve this without writing an excessive amount of code? If I just write in the query with comparison, will it screw up the return values if the user inputs only SOME values?
Thanks for your help.
Yes, it will screw up.
I would go with the ifs, I don't see what's wrong with them:
var query = table;
if(criteria1 != null)
query = query.Where(x => x.Value1 == criteria1);
if(criteria2 != null)
query = query.Where(x => x.Value2 == criteria2);
If you have a lot of criteria you could use expressions, a dictionary and a loop to cut down on the repetitive code.
In an ASP.NET MVC app, chances are your user input is coming from a form which is being POSTed to your server. In that case, you can make use of strongly-typed views, using a viewmodel with [Required] on the criteria that MUST be provided. Then you wrap your method in if (ModelState.IsValid) { ... } and you've excluded all the cases where the user hasn't given you something they need.
Beyond that, if you can collect your criteria into a list, you can filter it. So, you could do something like this:
filterBy = userValues.Where(v => v != null);
var Coll = (from obj in table where filterBy.Contains(value1) select obj);
You can make this more complex by having a Dictionary (or Lookup for non-unique keys) that contains a user-entered value along with some label (an enum, perhaps) that tells you which field they're filtering by, and then you can group them by that label to separate out the filters for each field, and then filter as above. You could even have a custom SearchFilter object that contains other info, so you can have filters with AND, NOT and OR conditions...
Failing that, you can remember that until you trigger evaluation of an IQueryable, it doesn't hit the database, so you can just do this:
var Coll = (from obj in table where value1 == requiredCriteria select obj);
if(criteria1 != null)
{
query = query.Where(x => x.Value1 == criteria1);
}
//etc...
if(criteria5 != null)
{
query = query.Where(x => x.Value5 == criteria5);
}
return query.ToList();
That first line applies any criteria that MUST be there; if there aren't any mandatory ones then it could just be var Coll = table;.
That will add any criteria that are provided will be applied, any that aren't will be ignored, you catch all the possible combinations, and only one query is made at the end when you .ToList() it.
As I understand of your question you want to centralize multiple if for the sake of readability; if I were right the following would be one of some possible solutions
Func<object, object, bool> CheckValueWithAnd = (x, y) => x == null ? true : x==y;
var query = from obj in table
where CheckValue(obj.value1, criteria1) &&
CheckValue(obj.value2, criteria2) &&
...
select obj;
It ls flexible because in different situations or scenarios you can change the function in the way that fulfill your expectation and you do not need to have multiple if.
If you want to use OR operand in your expression you need to have second function
Func<object, object, bool> CheckValueWithOr = (x, y) => x == null ? false : x==y;

Is this clear and efficient LINQ to join several tables/models and then group the results?

Is there another way to group the results of several joined models? Selecting each model into an anonymous type and then grouping works, but I don't know that it's the right way to do it.
All conditionals are in the three IQueryables I setup outside this query: attrDatas, dataIds, and filterIds.
var query = (
from a in attrDatas
join d in dataIds
on a.Id equals d.Id
join f in filterIds
on new { a.Id, a.AltId } equals new { f.Id, f.AltId }
select new
{
ad = a,
di = d,
//fi = f,
}
into grouped
group grouped by grouped.ad.AltId into g
select new VwModel
{
AltId = g.Key,
MaxReturn = g.Max(z => z.ad.Return),
PriceUsd = g.Max(z => z.ad.Price),
ApproxVal = g.Sum(z => (z.ad.Price*z.ad.Shares)),
HoldDate = g.Max(z => z.di.HoldDate),
});
I don't see any other way. Below the hood group by is equivalent to the GroupBy() extension method. Of each overload, the first input parameter is an IQueryable<TSource>, which is the only parameter that carries data. (The other parameters are Expressions that determine the grouping and the output). So this input list should contain everything you want to show in the result set after grouping.
Therefore you have to build an anonymous type (≠ generic, by the way). Using group a by a.AltId, for example, pushes d and f out of scope.

Resources