40_Version_control.asciidoc

Dealing with Conflicts

When updating a document with the index API, we read the original document, make our changes, and then reindex the whole document in one go. The most recent indexing request wins: whichever document was indexed last is the one stored in Elasticsearch. If somebody else had changed the document in the meantime, their changes would be lost.

Many times, this is not a problem. Perhaps our main data store is a relational database, and we just copy the data into Elasticsearch to make it searchable. Perhaps there is little chance of two people changing the same document at the same time. Or perhaps it doesn’t really matter to our business if we lose changes occasionally.

But sometimes losing a change is very important. Imagine that we’re using Elasticsearch to store the number of widgets that we have in stock in our online store. Every time that we sell a widget, we decrement the stock count in Elasticsearch.

One day, management decides to have a sale. Suddenly, we are selling several widgets every second. Imagine two web processes, running in parallel, both processing the sale of one widget each, as shown in Consequence of no concurrency control:

Figure 1. Consequence of no concurrency control

The change that web_1 made to the stock_count has been lost because web_2 is unaware that its copy of the stock_count is out-of-date. The result is that we think we have more widgets than we actually do, and we’re going to disappoint customers by selling them stock that doesn’t exist.

The more frequently that changes are made, or the longer the gap between reading data and updating it, the more likely it is that we will lose changes.

In the database world, two approaches are commonly used to ensure that changes are not lost when making concurrent updates:

Pessimistic concurrency control

Widely used by relational databases, this approach assumes that conflicting changes are likely to happen and so blocks access to a resource in order to prevent conflicts. A typical example is locking a row before reading its data, ensuring that only the thread that placed the lock is able to make changes to the data in that row.

Optimistic concurrency control

Used by Elasticsearch, this approach assumes that conflicts are unlikely to happen and doesn’t block operations from being attempted. However, if the underlying data has been modified between reading and writing, the update will fail. It is then up to the application to decide how it should resolve the conflict. For instance, it could reattempt the update, using the fresh data, or it could report the situation to the user.

Optimistic Concurrency Control

Elasticsearch is distributed. When documents are created, updated, or deleted, the new version of the document has to be replicated to other nodes in the cluster. Elasticsearch is also asynchronous and concurrent, meaning that these replication requests are sent in parallel, and may arrive at their destination out of sequence. Elasticsearch needs a way of ensuring that an older version of a document never overwrites a newer version.

When we discussed index, get, and delete requests previously, we pointed out that every document has a _version number that is incremented whenever a document is changed. Elasticsearch uses this _version number to ensure that changes are applied in the correct order. If an older version of a document arrives after a new version, it can simply be ignored.

We can take advantage of the _version number to ensure that conflicting changes made by our application do not result in data loss. We do this by specifying the version number of the document that we wish to change. If that version is no longer current, our request fails.

Let’s create a new blog post:

PUT /website/blog/1/_create
{
  "title": "My first blog entry",
  "text":  "Just trying this out..."
}

The response body tells us that this newly created document has _version number 1. Now imagine that we want to edit the document: we load its data into a web form, make our changes, and then save the new version.

First we retrieve the document:

GET /website/blog/1

The response body includes the same _version number of 1:

{
  "_index" :   "website",
  "_type" :    "blog",
  "_id" :      "1",
  "_version" : 1,
  "found" :    true,
  "_source" :  {
      "title": "My first blog entry",
      "text":  "Just trying this out..."
  }
}

Now, when we try to save our changes by reindexing the document, we specify the version to which our changes should be applied:

PUT /website/blog/1?version=1 (1)
{
  "title": "My first blog entry",
  "text":  "Starting to get the hang of this..."
}

1. We want this update to succeed only if the current _version of this document in our index is version 1.

This request succeeds, and the response body tells us that the _version has been incremented to 2:

{
  "_index":   "website",
  "_type":    "blog",
  "_id":      "1",
  "_version": 2
  "created":  false
}

However, if we were to rerun the same index request, still specifying version=1, Elasticsearch would respond with a 409 Conflict HTTP response code, and a body like the following:

{
  "error" : "VersionConflictEngineException[[website][2] [blog][1]:
             version conflict, current [2], provided [1]]",
  "status" : 409
}

This tells us that the current _version number of the document in Elasticsearch is 2, but that we specified that we were updating version 1.

What we do now depends on our application requirements. We could tell the user that somebody else has already made changes to the document, and to review the changes before trying to save them again. Alternatively, as in the case of the widget stock_count previously, we could retrieve the latest document and try to reapply the change.

All APIs that update or delete a document accept a version parameter, which allows you to apply optimistic concurrency control to just the parts of your code where it makes sense.

Using Versions from an External System

A common setup is to use some other database as the primary data store and Elasticsearch to make the data searchable, which means that all changes to the primary database need to be copied across to Elasticsearch as they happen. If multiple processes are responsible for this data synchronization, you may run into concurrency problems similar to those described previously.

If your main database already has version numbers—​or a value such as timestamp that can be used as a version number—​then you can reuse these same version numbers in Elasticsearch by adding version_type=external to the query string. Version numbers must be integers greater than zero and less than about 9.2e+18--a positive long value in Java.

The way external version numbers are handled is a bit different from the internal version numbers we discussed previously. Instead of checking that the current version is _the same as the one specified in the request, Elasticsearch checks that the current version is _less than the specified version. If the request succeeds, the external version number is stored as the document’s new _version.

External version numbers can be specified not only on index and delete requests, but also when creating new documents.

For instance, to create a new blog post with an external version number of 5, we can do the following:

PUT /website/blog/2?version=5&version_type=external
{
  "title": "My first external blog entry",
  "text":  "Starting to get the hang of this..."
}

In the response, we can see that the current _version number is 5:

{
  "_index":   "website",
  "_type":    "blog",
  "_id":      "2",
  "_version": 5,
  "created":  true
}

Now we update this document, specifying a new version number of 10:

PUT /website/blog/2?version=10&version_type=external
{
  "title": "My first external blog entry",
  "text":  "This is a piece of cake..."
}

The request succeeds and sets the current _version to 10:

{
  "_index":   "website",
  "_type":    "blog",
  "_id":      "2",
  "_version": 10,
  "created":  false
}

If you were to rerun this request, it would fail with the same conflict error we saw before, because the specified external version number is not higher than the current version in Elasticsearch.