I'm new to key value stores, but I'd like to learn. As a personal project, I'm trying to build an inventory management system with Node.js and Redis. Let's assume this is the correct technology to use for the moment.
If I had a simple system, that needs to track the number of widgets at a particular location, with the ability to look up details by widget or by location, my understanding according to https://matt.sh/thinking-in-redis-part-one is to store separate "custom indexes" to look up by location and by item.
In node.js to save a new entry then, we would create the entry with hmset, add the entry to the 2 indexes with sadd:
redis.hmset([
key,
'attr1', entry.attr1,
'attr2', entry.attr2,
'attr3', entry.attr3,
],
function(err) {
// add entry to location set
var locationKey = 'location:' + entry.location;
redis.sadd(locationKey, key, function(err) {
redis.expire(locationKey, 900);
});
// add entry to widget set
var widgetKey = 'widget:' + widget.id;
redis.sadd(widgetKey, key, function(err) {
redis.expire(widgetKey, 900);
});
redis.expire(key, 900);
}
);
Now if we wanted to move all widgets from one location to another, we'd need to get all entries from the widget set, add the entry to the new location index, and remove it from the old index:
// move all widgets to another location
redis.smembers('widget:' + widget.id, function(err, entryKeys) {
entryKeys.forEach(function(entryKey) {
// get entry for rebroadcast
redis.hgetall(entryKey, function(err, result) {
if (result) {
// add entry to new location's index
var locationKey = 'location:' + location;
redis.sadd(locationKey, entryKey, function(err) {
redis.expire(locationKey, 900);
});
// remove entry from old location's index
redis.srem('location:' + result.location, entryKey);
}
});
});
});
My concern is the number of requests that need to be made for each command. Adding an entry, will cost 3 inserts for the data itself, and 3 more assuming we want to expire the data. Moving all widgets will require 1+n inserts, n reads, and n deletes.
If this were for a real time game with hundreds or thousands of requests a second, is it ok for each command to require this many calls? Is this normal for a redis implementation?
Yes.
Redis is that fast. But do a benchmark on your machine, or similar production machine, that will run redis. It is included in redis itself.. (Post it back here, I'd be interested as well.)
Redis has a lot of commands at its disposal, and your data organization might allow cheaper calls, or calls-less-often. That will depend how you lay out the data model. There is not really a "query language" like SQL that can do lots of stuff in the query or combine queries into a single one. You are meant to hit redis a lot, which is a different philosophy than SQL (to some extent).
This personal project will allow you to see what works and what could be made better, so kudos on the effort. Good luck!
Related
I need to have 400+ price levels on Netsuite, but for the life of me, I can't find a way to add them through imports. From what I've seen and tried, Netsuite only allows you to upload items that reference existing price levels but doesn't allow you to upload new ones. Does anyone know how this could be done?
Price levels are scriptable.
Since this is just a one time job you could do this in a console window (inspect any editable standard record and find/show the console)
You will likely run into a governance error running this on 400 names but just
note the last name successfully created
refresh the page you have open
delete the names lines down through the last successful one
re-run the script
repeat until they are all created.
require(['N/record'], record=>{
const names = [
'Test Level 1' // use your whole list of names
'Test Level 2', // etc
];
names.forEach(n=>{
try{
const pr = record.create({type:'pricelevel'});
pr.setValue({fieldId:'name', value:n});
// make your array of names more complex to handle discounts etc.
//pr.setValue({fieldId:'discountpct', value:xx});
pr.save();
console.log('created', n);
}catch(e){
console.error(n, e);
}
});
console.log('done');
});
I have
db.result('DELETE FROM categories WHERE id = ${id}', category).then(function (data) { ...
and
db.many('SELECT * FROM categories').then(function (data) { ...
initially delete is called from one API call and then select on following API call, but callback for db request happens in reverse order, so I get list of categories with removed category.
Is there a way how to lock categories table with pg-promise?
If you want the result of the SELECT to always reflect the result of the previous DELETE, then you have two approaches to consider...
The standard approach is to unify the operations into one, so you end up executing all your dependent queries against the same connection:
db.task(function * (t) {
yield t.none('DELETE FROM categories WHERE id = ${id}', category);
return yield t.any('SELECT FROM categories');
})
.then(data => {
// data = only the categories that weren't deleted
});
You can, of course, also use either the standard promise syntax or even ES7 await/async.
The second approach would be to organize an artificial lock inside your service that would hold off on executing any corresponding SELECT until the DELETE requests are all done.
However, this is a very awkward solution, typically pointing at the flaw in the architecture. Also, as the author of pg-promise, I won't be even getting into that solution, as it would be way outside of my library anyway.
I'm using MongoDB with NodeJS. Therefore I use mongoose.
I'm developing a multi player real time game. So I receive many requests from many players sometimes at the very same time.
I can simplify it by saying that I have a house collection, that looks like this:
{
"_id" : 1,
"items": [item1, item2, item3]
}
I have a static function, called after each request is received:
house.statics.addItem = function(id, item, callback){
var HouseModel = this;
HouseModel.findById(id, function(err, house){
if (err) throw err;
//make some calculations such as:
if (house.items.length < 4){
HouseModel.findByIdAndUpdate(id, {$push: {items: item}}, cb);
}
});
}
In this example, I coded so that the house document can never have more than 4 items. But what happens is that when I receive several request at the very same time, this function is executed twice by both requests and since it is asynchronous, they both push a new item to the items field and then my house has 5 items.
I am doing something wrong? How can I avoid that behavior in the future?
yes, you need better locking on the houseModel, to indicate that an addItem
is in progress.
The problem is that multiple requests can call findById and see the same
house.items.length, then each determine based on that (outdated) snapshot
that it is ok to add one more item. The nodejs boundary of atomicity is the
callback; between an async call and its callback, other requests can run.
One easy fix is to track not just the number of items in the house but the
number of intended addItems as well. On entry into addItem, bump the "want
to add more" count, and test that.
One possible approach since the release of Mongoose 4.10.8 is writing a plugin which makes save() fail if the document has been modified since you loaded it. A partial example is referenced in #4004:
#vkarpov15 said:
8b4870c should give you the general direction of how one would write a plugin for this
Since Mongoose 4.10.8, plugins now have access to this.$where. For documents which have been loaded from the database (i.e., are not this.isNew), the plugin can add conditions which will be evaluated by MongoDB during the update which can prevent the update from actually happening. Also, if a schema’s saveErrorIfNotFound option is enabled, the save() will return an error instead of succeeding if the document failed to save.
By writing such a plugin and changing some property (such as a version number) on every update to the document, you can implement “optimistic concurrency” (as #4004 is titled). I.e., you can write code that roughly does findOne(), do some modification logic, save(), if (ex) retry(). If all you care about is a document remaining self-consistent and ensuring that Mongoose’s validators run and your document is not highly contentious, this lets you write code that is simple (no need to use something which bypasses Mongoose’s validators like .update()) without sacrificing safety (i.e., you can reject save()s if the document was modified in the meantime and avoid overwriting committed changes).
Sorry, I do not have a code example yet nor do I know if there is a package on npm which implements this pattern as a plugin yet.
I am also building a multiplayer game and ran into the same issue. I believe I have solved it my implementing a queue-like structure:
class NpcSaveQueue {
constructor() {
this.queue = new Map();
this.runQueue();
}
addToQueue(unitId, obj) {
if (!this.queue.has(unitId)) {
this.queue.set(String(unitId), obj);
} else {
this.queue.set(String(unitId), {
...this.queue.get(unitId),
...obj,
})
}
}
emptyUnitQueue(unitId) {
this.queue.delete(unitId);
}
async executeUnitQueue(unitId) {
await NPC.findByIdAndUpdate(unitId, this.queue.get(unitId));
this.emptyUnitQueue(unitId);
}
runQueue() {
setInterval(() => {
this.queue.forEach((value, key) => {
this.executeUnitQueue(key);
})
}, 1000)
}
}
Then when I want to update an NPC, instead of interacting with Mongoose directly, I run:
npcSaveQueue.addToQueue(unit._id, {
"location.x": newLocation.x,
"location.y": newLocation.y,
});
That way, every second, the SaveQueue just executes all code for every NPC that requires updating.
This function never executes twice, because update operation is atomic on a level of single document.
More info in official manual: http://docs.mongodb.org/manual/core/write-operations-atomicity/#atomicity-and-transactions
This may be a vary bad idea, or a possible solution that we have to a database concurrency problem.
We have a method that is called to do an update of a mongo record. We are seeing some concurrency problems - process A reads the record, process B reads the record, process A makes mods and saves the record, process makes B mods and saves the record. Because B reads after A, before A writes, it doesn't know about the changes A made, and we lose the data from A.
I'm wondering if we could not use a database semaphore, basically a field on the collection, that is a boolean. If we read the record at the start of the method, and the field is true, it's being edited. At that point, re-call the method using process.nexttick(), with the same data. Otherwise, set the semaphore, and carry on.
There would still be a bit of time between the read and the save, but it should be/could be faster than what we are doing now.
Be something like this. Any thoughts, anyone done anything like this? Will it even work?
function remove_source(service_id,session, next)
{
var User = Mongoose.model("User");
/* get the user, based on the session user id */
User.findById(session.me,function(err,user_info)
{
if (user_info.semaphore === true)
{
process.nextTick(remove_source(service_id,session,next));
}
else
{
user_info.semaphore = true;
user_info.save(function(err,user_new)
{
if (err) next(err,user_new);
else continue_on(null,user_new);
});
}
function continue_on(user_new)
{
etc.......
}
Edit: New Code:
The function now looks as follows. I'm doing individual updates to the arrays. This of course means that I now have the possibility, if the transaction fails between the first and second transactions, of having data out of sync. I'm thinking that I could simply resave the user object that I retrieved on entry into the function, overwriting my changes. I don't know if Mongoose/Mongo will not do the save if I have not changed that object, will have to try and see. Any more thoughts?
var User = Mongoose.model("User");
/* get the user, based on the session user id */
User.findById(session.me,function(err,user_info)
{
if (err)
{
next(err,user_info,null);
return;
}
if (!user_info || user_info.length === 0)
{
next(_e("ACCOUNT_NOT_FOUND"),"user_id: " + session.me);
return;
}
var source_service_info = _.where(user_info.credentials, {"source_service_id": service_id});
var source_service = source_service_info.source_service;
User.findByIdAndUpdate(session.me,{$pull: {"credentials": {"source_service_id": service_id}}},{},function(err,user_credential_removed)
{
if (err)
{
next(err,user_info,null);
return;
}
User.findByIdAndUpdate(session.me,{$pull: {"criteria": {"source_service": source_service}}},{},function(err,user_criteria_removed)
{
if (err)
{
next(err,user_info,null);
return;
}
else
{
next(null,user_criteria_removed);
}
});
});
});
};
The problem with your approach is that it just shortens the time during which the data could be read by a second process, it doesn't eliminate the problem.
The solution to this would be to set your semaphore in the same action as the read. I haven't used Mongoose, but in MongoDB you can use findAndModify to only return a User record if the semaphore is false, and if it is false, in one atomic operation, set the semaphore to true.
If you don't want to use findAndModify, you could first do an update that sets the semaphore true (or to some specific ID value so you know that it is YOUR semaphore) only if the semaphore is not set. Then, if that process succeeds, you could do the find (perhaps passing your semaphore ID as a criterion in the find). However, findAndModify, if it is available in Mongoose, would do that in one step.
A variation of that is described here: http://docs.mongodb.org/manual/tutorial/isolate-sequence-of-operations/ where you do a form of optimistic locking that checks that the old values are unchanged before changing them to the new values.
There is a variation on this that uses a separate table to simulate a two-phase commit: http://docs.mongodb.org/manual/tutorial/perform-two-phase-commits/
Edited: Upon interchange below, this seems to be a schema and updating issue. Question may become something like: I have some entries in an array, and the ordinal index to those entries relates to some other arrays as well. How do I perform deletes without having mismatches?
Three off the top possibilities occur, depending on frequency in the real world vs QA test scenarios.
Consider adding a deleted flag but keeping the records in the same order. If someone toggles, reuse the same record, but fix however you want.
Use an associative array (JS object) for each element (not a feature from relational world.) If you need an order, add an array that lists the keys in order. Both have syntax to update without touching anything other that what has changed, and will not overwrite changes to different fields.
Use an associative array where the keys are numbers. Actual deletion won't hurt retrieval.
stuff = {}
stuff[1] = {some:'details'}
stuff[2] = {some:'details2'}
Was
1) Are you making changes to the same field? Make that into an array, and push changes, and pop the latest to read the current value.
2) Are you changing different fields, but data is getting trounced? Then there is better syntax to use for the updating. you can update field by field.
$set: { 'fielda': 'valuea' }
won't lose edits on previous fields
3) change your schema
4) change the timing on the processes so they don't overlap. Or so they do so in smaller subsets, that you can manage to prevent from overlapping.
I'd like to know, just out of interest, what multiple processes are needed to make updates on the same record? I don't work with anything that looks like that.
I'm building a real-time feed application using Backbone.js, node.js and socket.io.
My Feed is a collection of Update models. Displaying these, overriding Backbone.sync for integration with socket.io works fine.
The complication comes in that each Update has a set of comments associated with it. When I show each Update in the Feed view, I want to show a summary of the associated comments (number of comments and a single 'most poular' comment), and also have the ability to click through to a different view to display each Update on its own with a paginated list of comments with further data.
I'm using backbone-relational to model the relationship between the Update model and Comment model, as follows:
Feed (collection) -> Update (model) -(has many)-> Comment (model)
I've been following this backbone-relational tutorial, but it seems to assume that I'd want to have all related data in memory at once in my Feed view, which I don't as there are potentially thousands of comments updating in real-time:
http://antoviaque.org/docs/tutorials/backbone-relational-tutorial/
My questions are:
How can I bring in summary data for comments to each Update in my Feed view without loading all comment data, and also maintain the ability to show paginated full data in my Update view?
I'm using backbone.layoutmanager for rendering my views. How best should I break my views up to accomplish the above?
For Q1:
I'm assuming you're using something like ioSync to use socket.io in Backbone.sync instead of REST API, or a similar solution.
Include metadata (such as # of comments) as an attribute on Update. If your Update object is heavy weight in itself, you could update the count using ioBind and custom server-side socket.io events instead of sending the whole object every time.
Include an attribute topComment as an additional one-to-one relation in Update. When initially loading Update from the server, include topComment in the response, but not the other comments.
Lazy-load the rest of the comments using custom socket.io events. You will likely want a server-side handler that takes as parameters updateId, startIndex, maxComments, which returns a list of comments for the given Update starting at the given index. If the result is sent to the client as JSON, then it's easy to do something like this on the client:
// Assume `model` is an instance of `Update`.
socket.emit('get_comments_page', {
updateId: model.get('id'),
startIndex: 1,
maxComments: 10
}, function(err, data) {
if (err) {
alert('Unable to fetch comments: ', err);
} else {
model.get('messages').reset(data)
}
});
Avoid sending ID for all comments when fetching Update then trying to use fetchRelated to resolve them. I learned this one the hard way :O/
You could also store the comments collection directly on the view without associating it as relationship of Update
For Q2:
I don't have any experience with layoutmanager as I use Backbone.Marionette for managing my views. Marionette has an async extension (disclaimer: I'm a co-maintainer). I encourage to see how Marionette.async does the delayed rendering, waiting for the data to arrive from the server.
The main idea is to use jquery's Deferred objects that resolve when the data comes back from the server. Extending the above example with deferred:
var MyView = Backbone.View.extend({
// ... normal stuff that views need ...
initialize: function() {
var deferred = $.Deferred();
// Assume `model` is an instance of `Update`.
var that = this;
socket.emit('get_comments_page', {
updateId: that.model.get('id'),
startIndex: that.options.pageNumber,
maxComments: 10
}, function(err, data) {
if (err) {
alert('Unable to fetch comments: ', err);
} else {
that.model.get('messages').reset(data)
}
deferred.resolve();
});
this.promise = deferred.promise();
},
render: function() {
var that = this;
this.promise.done(function() {
// Do your normal rendering code here, for instance:
$(that.el).html(that.template(that.model.toJSON()));
});
return this;
}
});
Note: the code snippets above are not tested as is.