I've crawled all over stack overflow, and have not found any info on how to return proper pagination data included in the resultset.
I'm trying to aggregate some data from my mongo store. What I want, is to have something return:
{
total: 5320,
page: 0,
pageSize: 10,
data: [
{
_id: 234,
currentEvent: "UPSTREAM_QUEUE",
events: [
{ ... }, { ... }, { ... }
]
},
{
_id: 235,
currentEvent: "UPSTREAM_QUEUE",
events: [
{ ... }, { ... }, { ... }
]
}
]
}
This is what I have so far:
// page and pageSize are variables
db.mongoAuditEvent.aggregate([
// Actual grouped data
{"$group": {
"_id" : "$corrId",
"currentEvent": {"$last": "$event.status"},
"events": { $push: "$$ROOT"}
}},
// Pagination group
{"$group": {
"_id": 0,
"total": { "$sum": "corrId" },
"page": page,
"pageSize": pageSize,
"data": {
"$push": {
"_id": "$_id",
"currentEvent": "$currentEvent",
"events": "$events"
}
}
}},
{"$sort": {"events.timestamp": -1} }, // Latest first
{"$skip": page },
{"$limit": pageSize }
], {allowDiskUse: true});
I'm trying to have a pagination group as root, containing the actual grouped data inside (so that I get actual totals, whilst still retaining skip
and limits
).
The above code will return the following error in mongo console:
The field 'page' must be an accumulator object
If I remove the page
and pageSize
from the pagination group, I still get the following error:
BSONObj size: 45707184 (0x2B96FB0) is invalid. Size must be between 0 and 16793600(16MB) First element: id: 0
If I remove the pagination group alltogether, the query works fine. But I really need to return how many documents I have stored total
, and allthough not actually necessary, page
and pageSize
would be nice to return as well.
Can somebody please tell me what I am doing wrong? Or tell me if it is at all possible to do this in one go?
The MongoDB $count operator allows us to pass a document to the next phase of the aggregation pipeline that contains a count of the documents. There a couple of important things to note about this syntax: First, we invoke the $count operator and then specify the string.
3, it was seen that MongoDB is typically faster on more complex queries. It's faster from disk when there are no indexes, whereas MySQL is faster from RAM. BI Connector is slower for simple queries and not as fast as hand-crafted aggregation.
If you have a lot of events, {$ push: "$$ ROOT"}, will make Mongo return an error, I have solved it with $facet (Only works with version 3.4+)
aggregate([
{ $match: options },
{
$facet: {
edges: [
{ $sort: sort },
{ $skip: skip },
{ $limit: limit },
],
pageInfo: [
{ $group: { _id: null, count: { $sum: 1 } } },
],
},
},
])
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With