Suppose this is my data:
{
"info": [
{
"name": "Dr. DRE"
}
]
}
How do I query in Cassandra all rows that have "Dr. DRE" as name?
select * where ..?
I have no idea, and didn't find anything useful on google...
Since we clarified that you're using usergrid and not a native Cassandra instance, this should work for you:
where info.name='Dr. DRE'
(Note that in Usergrid 1.0, select * is implied, but you can include it if you like)
While the use of the = in this case may seem a little strange, you can use that to look for values in an array.
In Cassandra 2.1 and above you can index the collection and query the collection using a contains in the where clause. Read more here and here
Related
I have the following query:
SELECT *
FROM table
WHERE (id, other_id, status)
IN (
(1, 'XYZ', 'OK'),
(2, 'ZXY', 'OK') -- , ...
);
Is it possible to construct this query in a type-safe manner using jOOQ, preferably without generating composite keys? Is it possible to do this using jOOQ 3.11?
My apologies, it seems my Google-fu was not up to par. The opposite of this question can be found here: Use JOOQ to do a delete specifying multiple columns in a "not in" clause
For completeness' sake, so that other Google searches might be more immediately helpful, the solution is:
// can be populated using DSL.row(...); for each entry
Collection<? extends Row3<Long, String, String>> values = ...
dslContext.selectFrom(TABLE)
.where(DSL.row(ID, OTHER_ID, STATUS).in(values))
.fetch();
Relevant jOOQ documentation: https://www.jooq.org/doc/3.14/manual/sql-building/conditional-expressions/in-predicate-degree-n/
Your own answer already shows how to do this with a 1:1 translation from SQL to jOOQ using the IN predicate for degrees > 1.
Starting from jOOQ 3.14, there is also the option of using the new <embeddablePrimaryKeys/> flag in the code generator, which will produce embeddable types for all primary keys (and foreign keys referencing them). This will help never forget a key column on these queries, which is especially useful for joins.
Your query would look like this:
ctx.selectFrom(TABLE)
.where(TABLE.PK_NAME.in(
new PkNameRecord(1, "XYZ", "OK"),
new PkNameRecord(2, "ZXY", "OK")))
.fetch();
The query generated behind the scenes is the same as yours, using the 3 constraint columns for the predicate. If you add or remove a constraint from the key, the query will no longer compile. A join would look like this:
ctx.select()
.from(TABLE)
.join(OTHER_TABLE)
.on(TABLE.PK_NAME.eq(OTHER_TABLE.FK_NAME))
.fetch();
Or an implicit join would look like this:
ctx.select(OTHER_TABLE.table().fields(), OTHER_TABLE.fields())
.from(OTHER_TABLE)
.fetch();
Lets say I have these documents in my CosmosDB. (DocumentDB API, .NET SDK)
{
// partition key of the collection
"userId" : "0000-0000-0000-0000",
"emailAddresses": [
"someaddress#somedomain.com", "Another.Address#someotherdomain.com"
]
// some more fields
}
I now need to find out if I have a document for a given email address. However, I need the query to be case insensitive.
There are ways to search case insensitive on a field (they do a full scan however):
How to do a Case Insensitive search on Azure DocumentDb?
select * from json j where LOWER(j.name) = 'timbaktu'
e => e.Id.ToLower() == key.ToLower()
These do not work for arrays. Is there an alternative way? A user defined function looks like it could help.
I am mainly looking for a temporary low-effort solution to support the scenario (I have multiple collections like this). I probably need to switch to a data structure like this at some point:
{
"userId" : "0000-0000-0000-0000",
// Option A
"emailAddresses": [
{
"displayName": "someaddress#somedomain.com",
"normalizedName" : "someaddress#somedomain.com"
},
{
"displayName": "Another.Address#someotherdomain.com",
"normalizedName" : "another.address#someotherdomain.com"
}
],
// Option B
"emailAddressesNormalized": {
"someaddress#somedomain.com", "another.address#someotherdomain.com"
}
}
Unfortunately, my production database already contains documents that would need to be updated to support the new structure.
My production collections contain only 100s of these items, so I am even tempted to just get all items and do the comparison in memory on the client.
If performance matters then you should consider one of the normalization solution you have proposed yourself in question. Then you could index the normalized field and get results without doing a full scan.
If for some reason you really don't want to retouch the documents then perhaps the feature you are missing is simple join?
Example query which will do case-insensitive search from within array with a scan:
SELECT c FROM c
join email in c.emailAddresses
where lower(email) = lower('ANOTHER.ADDRESS#someotherdomain.com')
You can find more examples about joining from Getting started with SQL commands in Cosmos DB.
Note that where-criteria in given example cannot use an index, so consider using it only along another more selective (indexed) criteria.
TLDR
Is there a way to limit queryByExample to a collection in NodeJS?
Problem faced
I have a complex query with some optional fields (i.e. sometimes some search fields will be omitted). So I need to create a query dynamically, e.g. in JSON. QueryByExample seems to be the right tool to use here as it gives me that flexibility to pass a JSON. However my problem is that I would like to limit my search to only one collection or directory.
e.g. I was hoping for something like
searchJSON = {
title: { $word: "test" },
description: { $word: "desc" }
};
//query
db.documents.query(qb.where(
qb.collection("collectionName"),
qb.byExample(searchJSON)
)).result()...
In this case searchJSON could have been built dynamically, for example maybe sometimes title may be omitted from the search.
This doesn't work because the query builder only allows queryByExample to be the only query. But I'd instead like to built a dynamic search query which is limited to a collection or directory.
At present, I think you would have to express the query with QueryBuilder instead of Query By Example using
qb.and([
qb.collection('collectionName'),
qb.word('title', 'test'),
qb.word('description', 'desc')
])
See http://docs.marklogic.com/jsdoc/queryBuilder.html#word
That said, it should be possible for the Node.js API to relax that restriction based on the fixes in MarkLogic 9.0-2
Please file an issue on https://github.com/marklogic/node-client-api
I'm using Node.js + mongodb. I have few documents in my collection and i want to know does my collection have any document matched my condition. Of course i can simply use
myModel.find({ myField: someValue }) and check is anything comes or not. But i want to use solution like sql provides exists keyword? Help me, please
Edit: my bad. I forget to tell that "performance first".
MongoDB's $exists actually doesn't help you very much to find out if a certain document exists in your collection. It is used for example to give you all documents that have a specific field set.
MongoDB has no native support for an sql like exists. What you can use, however, is myModel.findOne({ myField: someValue }) and then check if it is null.
To enhance performance you can tell MongoDB to only load the object id via projection, like this:
myModel.findOne({ myField: someValue }, {_id: 1})
There is an exist mechanism in mongodb, I'll demonstrate a sample below.
For example below, I'm looking for records that have tomato.consensus fields and that it's empty, so I can delete them or avoid them. In case I was looking for "tomato.consensus": Dublin, I'd change Null to Dublin, to match that.
I hope this is helpful, if not fire away any questions
tomato
----consensus
db.movieDetails.updateMany({$and: [
{"tomato.consensus": {$exists: true} },
{"tomato.consensus": null} ] },
]})
Current MongoDB documentation states the following:
You may only have 1 geospatial index per collection, for now. While
MongoDB may allow to create multiple indexes, this behavior is
unsupported. Because MongoDB can only use one index to support a
single query, in most cases, having multiple geo indexes will produce
undesirable behavior.
However, when I create two geospatial indices in a collection (using Mongoose), they work just fine:
MySchema.index({
'loc1': '2d',
extraField1: 1,
extraField2: 1
});
MySchema.index({
'loc2': '2d',
extraField1: 1,
extraField2: 1
});
My question is this: while it seems to work, the MongoDB documentation says this could "produce undesirable behavior". So far, nothing undesirable has not yet been discovered neither in testing or use.
Should I be concerned about this? If the answer is yes then what would you recommend as a workaround?
It is still not supported, so even although you can create two of them, it doesn't mean they are actually used properly. I would investigate explain output, on the mongo shell and issue a few queries that make use of the loc and loc2 fields in a geospatial way. For example with:
use yourDbName
db.yourCollection.find( { loc: { $nearSphere: [ 0, 0 ] } } ).explain();
and:
db.yourCollection.find( { loc2: { $nearSphere: [ 0, 0 ] } } ).explain();
And then compare what the explain information gives you. You will likely see that only the first created geo index is used for both searches. There are a few tickets in JIRA for this that you might want to vote on:
https://jira.mongodb.org/browse/SERVER-2331
https://jira.mongodb.org/browse/SERVER-3653