In this post we describe an approach to solve the problem of an application that requires both Full and Atomic Updates, using one of the powerful concepts in Object Oriented Programming: Polymorphism.
In Object-Oriented Programming, Polymorphism refers to the ability of a variable, method or object to take on multiple forms.
Although the example context has been abstracted in order to provide a high-level perspective, a practical application of the described approach has been implemented in Alfresco Search Services [1].
Alfresco Search Services provides search capabilities to Alfresco Content Services by leveraging Apache Solr.
It is used by both Enterprise and Community releases of Alfresco Content Services.
Context
The existing code creates SolrInputDocument instances from an incoming data model. Once created, documents are sent to Solr for indexing.
Each document represents the full state of a domain object: that means the very first time it is sent, it will be inserted; the following time the same document (i.e. a document with the same id) is sent, it replaces the existing document.
This is a core part of the system, and the logic is quite complex: a SolrInputDocument instance is created in several places and passed around a lot of methods that enrich it with a specific set of attributes. Something like this:
public void indexScenario1(DomainObject o) {
SolrInputDocument doc = new SolrInputDocument();
...
addAttributeSetA(doc, Domain);
addAttributeSetB(doc, Domain);
if (something)
addAttributeSetC(doc, Domain);
else
addAttributeSetD(doc, Domain);
... Challenge
With our contribution the part of the system that creates the domain model instances changed a bit: the main improvement consists of the additional capability to work with “delta” objects. In other words, the caller code is able to provide to that indexing component either “full” or “partial” domain objects (i.e. domain objects containing only things that have been updated).
Constraints
So far, you think that this is a perfect fit for using atomic updates! Definitely true: the domain objects that contain only the changed bits can be transformed in partial SolrInputDocument instances, and then sent to Solr for indexing.
However, a first constraint needs to be addressed: the partial objects won’t be an exclusive scenario, we will still have to deal with full objects.
Second constraint: as said above, the indexing component represents a central/critical part of the system so even a minimal change carries on a certain level of risk so the code changes should be minimised.
In our experience that requires a “the less you change, the better” approach, and the old good Object Oriented Programming is definitely great at it!
What are Atomic Updates?
Atomic Updates [2] are a way to execute indexing commands client side using an “update” semantic, by applying/indexing a document representing a partial state of a domain object.
So practically, using Atomic Updates a client is able to send only a “partial” document that contains only the updates that need to be applied on an existing (i.e. previously indexed) document.
Let’s see an example. After indexing the following document:
{
"id": 1
"title": "Design Patterns: Elements of Reusable Object-Oriented Software",
"author": [
"Erich Gamma",
"Richard Helm",
"Ralph Jonson"
]
} You realise a missing “h” in “Ralph Johnson” (aaaarrgh! Mistaking the name of such a Guru: unacceptable!); in addition, you forgot John Vlissides…what a disaster!
So you can do one of the following two things.
The usual way consists of recreating the whole document without the mistake and re-send it to Solr:
{
"id":1
"title":"Design Patterns: Elements of Reusable Object-Oriented Software",
"author":[
"Erich Gamma",
"Richard Helm",
"Ralph Johnson",
"John Vlissides"
]
}
That new document completely replaces the indexed one (note: implicit assumption is that the uniqueId field is “id”).
The other way allows us to send only things we want to change on an existing document. In this case we would send to Solr a document like this:
{
"id": 1
"author": {
"remove": "Ralph Jonson",
"add": ["Ralph Johnson", "John Vlissides"]
}
} It will target the indexed document with id=1 and
- it removes the wrong value (“Ralph Jonson”)
- it adds the correct value for the author (“Ralph Johnson”)
- it adds the other missing author
As you can see, the value of a field that needs to be updated is no longer a literal value (e.g. a String, an Integer) or a list of values; instead we have a map where keys are the update commands we want to apply (e.g. remove, add, set) and values are one or more literal values we want to use for the update.
More information about the whole semantic of the AtomicUpdates can be found in the Apache Solr Reference Guide[2]: here it is important to remember that Solr side, there’s no a “true” partial update happening behind the scenes: the old version of the document is fetched and it is merged with the partial state; after that, the new “full” resulting document is indexed again.
Still it is hugely beneficial as it reduced a lot the amount of data you may transfer to Solr when you need to update documents.
In Java, specifically in SolrJ, the SolrInputDocument class represents data we send to Solr for indexing. That is basically a Map so we can add, set or remove fields and values.
We are interested in the following three methods:
// If a field with that name doesn’t exist it adds a new entry with the // corresponding value, otherwise the value is collected together with // the existing value(s) // This is typically used on multivalued fields (i.e. calling twice this // method on the same field, will collect 2 xvalues for that field) addField(String name, Object value) // Sets/Replaces a field value setField(String name, Object value) // Remove a field from the document removeField(String name, Object value)
The same class is also used for representing a partial document. You can do that by setting a map as value in the setField or addField method. The map can have one or more modifiers:
-
- “add”: adds the specified values to a multiValued field.
- “remove”: removes all occurrences of the specified values from a multiValued field.
- “set”: sets or replaces the field value(s) with the specified value(s), or removes the values if ‘null’ or empty list is specified as the new value.
Note there are two additional modifiers (inc, removeregex) but we are not interested on them in this context.
The Idea
Remember the constraints we put above:
-
- the existing code always does full document updates
- a change has been implemented on the caller side: incoming domain objects will be full or partial, depending on the use case
- the Solr document instance valorisation is spread across a lot of methods. A SolrInputDocument instance is created and then passed on several methods that set some part of the document state.
- we need partial updates but they won’t be the exclusive scenario: in some cases we still have full updates
Implementing in Java the partial update mechanism described so far requires that the methods addField, setField or removeField are aware of their context of execution (partial or full update).
That because in case of a full update, adding a new author would simply be
doc.addField(“author”, “Ralph Johnson”);
while in a partial update, it is necessary to take into account the difference between the very first time the add happened:
List<String> authors = new ArrayList();
authors.add(“Ralph Johnson”);
doc.addField(“author”, new HashMap() {{ “add”, authors}}; from the subsequent times:
Map<String, Object> fieldModifier =
(Map<String,Object>)doc.getFieldValue(“author);
List<String> authors = (List<String>) fieldModifier.get(“add”);
authors.add(“John Vlissides”); The logic above (that could be written definitely better) needs to be done for field, for each add/set/remove call! Is there a better way to deal with this? Yes, of course:
creating a subclass of SolrInputDocument:
public class PartialSolrInputDocument extends SolrInputDocument {
static Function<String, List<Object>> LAZY_EMPTY_MUTABLE_LIST =
key -> new ArrayList<>();
@Override
@SuppressWarnings("unchecked")
public void addField(String name, Object value) {
Map<String, List<Object>> fieldModifier =
(Map<String, List<Object>>)computeIfAbsent(name, k -> {
remove(name);
setField(name, newFieldModifier("add"));
return getField(name);
}).getValue();
ofNullable(value)
.ifPresent(v ->
fieldModifier.computeIfAbsent(
fieldModifier
.keySet()
.iterator()
.next(),
LAZY_EMPTY_MUTABLE_LIST).add(v));
}
@Override
public SolrInputField removeField(String name) {
setField(name, newFieldModifier("set"));
return getField(name);
}
private Map<String, List<String>> newFieldModifier(String op) {
return new HashMap<>()
{{
put(op, null);
}};
}
} the logic of this class can be summarised as follows:
-
- setField: it maintains the original semantic: calling this method will replace any existing value
- removeField: a removeField on a partial document means “Hey, I want to remove any existing value from the indexed document”. This semantic is implemented in atomic updates using a “set” modifier with a null value
- addField: the logic here changes depending if a call “removeField” previously happened or not (on a given field).
- If a removeField happened for field X, it is associated with a “set” modifier and a null value. Then “addField” is called, the added value(s) populates the list associated with that “set” modifier. In other words, the meaning is “Solr, take this field definition and use it for replacing the existing values in the indexed document”.
- else (a removeField DID NOT happen for field X): addField collects a set of values in the “add” field modifier. In other words the collected values are added to the existing value(s) in the indexed document.
Using this approach, the question: shall we use a full or a partial update? is solved at object construction time.
Let’s see an example. The following is an existing method which uses an input SolrInputDocument instance and adds a new name to the multiValued field “author”:
public void addAuthor(SolrInputDocument doc, String authorName) {
doc.addField(“author”, authorName)
} Now, assuming the method that creates the SolrInputDocument instance is aware of the context (full or a partial update):
// In case of full document update SolrInputDocument doc = new SolrInputDocument();
or
// in case of partial document update (i.e. atomic update) SolrInputDocument doc = new PartialInputDocument();
and then, regardless the previous choice, the following method behaves correctly:
addAuthor(doc, “Ralph Johnson”);
depending on the passed SolrInputDocument instance type, the proper addField method is called, and the resulting document triggers a full or a partial update. The same is valid for all other methods that populate the document state.
It’s important to underline that no change happened to the signature of those methods, polimorphism manages the correct implementation depending on the type.
As a side note, please keep in mind that the SolrInputDocument (and therefore the PartialSolrinputDocument subclass) is a potential good candidate for being a Fragile class [3].
This means that what is described above is not intended to act as a general-purposes solution which fits any possible scenario.
Shameless plug for our training and services!
Did I mention we do Apache Solr Beginner and Elasticsearch Beginner training?
We also provide consulting on these topics, get in touch if you want to bring your search engine to the next level!
Subscribe to our newsletter
Did you like this post about Atomic updates? Don’t forget to subscribe to our Newsletter to stay always updated from the Information Retrieval world!
