Operations

This module contains the Operation interfaces and core operation implementations.

It is assumed that all Gaffer graphs will be able to handle these core operations.

An Operation implementation defines an operation to be processed on a graph, or on a set of results which are returned by another operation. An Operation class contains the configuration required to tell Gaffer how to carry out the operation. For example, the AddElements operation contains the elements to be added. The GetElements operation contains the seeds to use to find elements in the graph and the filters to apply to the query. The operation classes themselves should not contain the logic to carry out the operation (as this may vary between the different supported store types), just the configuration.

For each operation, each Gaffer store will have an OperationHandler, where the processing logic is contained. This enables operations to be handled differently in each store.

Operations can be chained together to form an OperationChain. When an operation chain is executed on a Gaffer graph the output of one operation is passed to the input of the next.

An OperationChain.Builder is provided to help with constructing a valid operation chain - it ensures the output type of an operation matches the input type of the next.

How to write an Operation

Operations should be written to be as generic as possible to allow them to be applied to different graphs/stores.

Operations must be JSON serialisable in order to be used via the REST API

  • i.e. there must be a public constructor and all the fields should have getters and setters.

Operation implementations need to implement the Operation interface and the extra interfaces they wish to make use of. For example an operation that takes a single input value should implement the Input interface.

Here is a list of some of the common interfaces:

  • uk.gov.gchq.gaffer.operation.io.Input
  • uk.gov.gchq.gaffer.operation.io.Output
  • uk.gov.gchq.gaffer.operation.io.InputOutput - Use this instead of Input and Output if your operation takes both input and output.
  • uk.gov.gchq.gaffer.operation.io.MultiInput - Use this in addition if you operation takes multiple inputs. This will help with JSON serialisation
  • uk.gov.gchq.gaffer.operation.SeedMatching
  • uk.gov.gchq.gaffer.operation.Validatable
  • uk.gov.gchq.gaffer.operation.graph.OperationView
  • uk.gov.gchq.gaffer.operation.graph.GraphFilters
  • uk.gov.gchq.gaffer.operation.graph.SeededGraphFilters

Each operation implementation should have a corresponding unit test class that extends the OperationTest class.

Operation implementations should override the close method and ensure all closeable fields are closed.

Any fields that are required should be annotated with the Required annotation.

All implementations should also have a static inner Builder class that implements the required builders. For example:

public static class Builder extends Operation.BaseBuilder<GetElements, Builder>
        implements InputOutput.Builder<GetElements, Iterable<? extends ElementId>, CloseableIterable<? extends Element>, Builder>,
        MultiInput.Builder<GetElements, ElementId, Builder>,
        SeededGraphFilters.Builder<GetElements, Builder>,
        SeedMatching.Builder<GetElements, Builder>,
        Options.Builder<GetElements, Builder> {
    public Builder() {
            super(new GetElements());
    }
}

Lazy Results

Operation results are lazy (where possible) so that results are lazily loaded whilst a user consumes each result.

For example if a user executes a GetAllElements on Accumulo:

final Iterable<? extends Element> elements = graph.execute(new GetAllElements(), getUser());

The 'elements' iterable is lazy and the query is only executed on Accumulo when you start iterating around the results. If you iterate around the results a second time, the query on Accumulo will be executed again.

If you add another element 'X' to the graph before you consume the 'elements' iterable you will notice the results now also contain 'X'.

For this reason you should be very careful if you do an AddElements with a lazy iterable returned from a Get query on the same Graph. The problem that could arise is that the AddElements will lazily consume the lazy iterable of elements, potentially causing duplicates to be added.

To do a Get followed by an Add on the same Graph, we recommend consuming and caching the Get results first. For a small number of results, this can be done simply using the ToList operation in your chain. e.g:

new OperationChain.Builder()
                .first(new GetAllElements())
                .then(new ToList<>())
                .then(new AddElements())
                .build();

For a large number of results you could add them to the gaffer cache temporarily:

new OperationChain.Builder()
                .first(new GetAllElements())
                .then(new ExportToGafferResultCache<>())
                .then(new DiscardOutput())
                .then((Operation) new GetGafferResultCacheExport())
                .then(new AddElements())
                .build()

FAQs

Here are some frequently asked questions.

If I do a query like GetElements or GetAdjacentIds the response type is a CloseableIterable - why?

To avoid loading all the results into memory, Gaffer stores should return an iterable that lazily loads and returns the data as a user iterates around the results. In the cases of Accumulo and HBase this means a connection to Accumulo/HBase must remain open whilst you iterate around the results. This closeable iterable should automatically close itself when you get to the end of the results. However, if you decide not to read all the results, i.e you just want to check if the results are not empty !results.iterator().hasNext() or an exception is thrown whilst iterating around the results, then the results iterable will not be closed and hence the connection to Accumulo/HBase will remain open. Therefore, to be safe you should always consume the results in a try-with-resources block.

Following on from the previous question, why can't I iterate around the results in parallel?

As mentioned above the results iterable holds a connection open to Accumulo/HBase. To avoid opening multiple connections accidentally leaving the connections open, the Accumulo and HBase stores only allow one iterator to be active at a time. When you call .iterator() the connection is opened. If you call .iterator() again, the original connection is closed and a new connection is opened. This means you can't process the iterable in parallel using Java 8's streaming api. If the results will fit in memory you could add them to a Set/List and then process that collection in parallel.

How do I return all my results summarised?

You need to provide a View to override the groupBy fields for all the element groups defined in the Schema. If you set the groupBy field to an empty array it will mean no properties will be included in the element key, i.e all the properties will be summarised. You can do this be provided a View like this:

"view": {
    "globalElements" : [{
        "groupBy" : []
    }]
}

My queries are returning duplicate results - why and how can I deduplicate them?

For example, if you have a Graph containing the Edge A-B and you do a GetElements with a large number of seeds, with the first seed A and the last seed B, then you will get the Edge A-B back twice. This is because Gaffer stores lazily return the results for your query to avoid loading all the results into memory so it will not realise the A-B has been queried for twice.

You can deduplicate your results in memory using the ToSet operation. But, be careful to only use this when you have a small number of results. It might be worth also using the Limit operation prior to ToSet to ensure you don't run out of memory.

e.g:

new OperationChain.Builder()
    .first(new GetAllElements())
    .then(new Limit<>(1000000))
    .then(new ToSet<>())
    .build();

I have just done a GetElements and now I want to do a second hop around the graph, but when I do a GetElements followed by another GetElements I get strange results.

You can seed a get related elements operation with vertices (EntityIds) or edges (EdgeIds). If you seed the operation with edges you will get back the Entities at the source and destination of the provided edges, in addition to the edges that match your seed.

For example, using this graph:


    --> 4 <--
  /     ^     \
 /      |      \
1  -->  2  -->  3
         \
           -->  5

If you start with seed 1 and do a GetElements (related) then you would get back:

1
2
4
1 -> 2
1 -> 4

If you chain this into another GetElements then you would get back some strange results:

#Seed 1 causes these results
1
2
1 -> 2
1 -> 4

#Seed 2 causes these results
2
1
3
4
5
1 -> 2
2 -> 3
2 -> 4
2 -> 5

#Seed 4 causes these results
4
1
2
3
1 -> 4
2 -> 4
3 -> 4

#Seed 1 -> 2 causes these results
1
2
1 -> 2

#Seed 1 -> 4 causes these results
1
4
1 -> 4

So you get a lot of duplicates and unwanted results. What you really want to do is to use the GetAdjacentIds query to simply hop down the first edges and return just the vertices at the opposite end of the related edges. You can still provide a View and apply filters to the edges you traverse down. In addition it is useful to add a direction to the query so you don't go back down the original edges. So let's say we only want to traverse down outgoing edges. Doing a GetAdjacentIds with seed 1 would return:

2
4

Then you can do another GetAdjacentIds and get the following:

#Seed 2 causes these results
4
5

#Seed 4 does not have any outgoing edges so it doesn't match anything

You can continue doing multiple GetAdjacentIds to traverse around the Graph further. If you want the properties on the edges to be returned you can use GetElements in your final operation in your chain.

Any tips for optimising my queries?

Limit the number of groups you query for using a View - this could result in a big improvement.

When defining filters in your View try and use the preAggregationFilter for all your filters as this will be run before aggregation and will mean less work has to be done to aggregate properties that you will later just discard. On Accumulo and HBase, postTransformFilters are not distributed, the are computed on a single node so they can be slow.

Some stores (like Accumulo) store the properties in different columns and lazily deserialise a column as properties in that column are requested. So if you limit your filters to just 1 column then less data needs to be deserialised. For Accumulo and HBase the columns are split up depending on whether the property is a groupBy property, the visibilityProperty and the remaining. So if you want to execute a time window query and your timestamp is a groupBy property then depending on the store you are running against this may be optimised. On Accumulo this will be fast as it doesn't need to deserialise the entire Value, just the column qualifier containing your timestamp property.

Also, when defining the order of Predicates in a Filter, the order is important. It will run the predicates in the order your provide so order them so that the first ones are the more efficient and will filter out the most data. It is generally more efficient to load/deserialise the groupBy properties than the non-groupBy properties, as there are normally less of them. So if your filter applies to 2 properties, a groupBy and a non-groupBy property, then we recommend putting the groupBy property filter first as that will normally be more efficient.

When doing queries, if you don't specify Pre or Post Aggregation filters then this means the entire filter can be skipped. When running on stores like Accumulo this means entire iterators can be skipped and this will save a lot of time. So, if applicable, you will save time if you put all your filtering in either the Pre or Post section (in some cases this isn't possible).

Gaffer lets you specify validation predicates in your Schema to validate your data when added and continuously in the background for age off. You can optimise this validation, by removing any unnecessary validation. You can do most of the validation you require in your ElementGenerator class when you generate your elements. The validation you provide in the schema should be just the validation that you actually have to have, because this may be run A LOT. On Accumulo - it is run in major/minor compactions and for every query. If you can, just validate properties that are in the groupBy, this will mean that the store may not need to deserialise all of the other properties just to perform the validation.

How can I optimise the GetAdjacentIds query?

When doing GetAdjacentIds, try and avoid using PostTransformFilters. If you don't specify these then the final part of the query won't need to deserialise the properties it can just extract the destination off the edge. Also see the answer above for general query optimisation.

How can I optimise my AddElementsFromHdfs?

Try using the SampleDataForSplitPoints and SplitStore operations to calculate splits points. These can then be used to partition your data in the map reduce job used to import the data. If adding elements into an empty Accumulo table or a table without any splits then the SampleDataForSplitPoints and SplitStore operations will be executed automatically for you. You can also optionally provide your own splits points for your AddElementsFromHdfs operation.

I want to filter the results of my query based on the destination of the result Edges

OK, there are several ways of doing this and you will need to chose the most appropriate way for your needs. Also worth reading GetElements example.

If you are querying with just a single EntitySeed with a vertex value of X and require the destination to be Y then you should change your query to use an EdgeSeed with source = X and destination = Y and directedType = EITHER.

If you are querying with multiple EntitySeeds then just change each seed into an EdgeSeed as described above.

If you require your destination to match a provided regex than you will need to use the regex filter: uk.gov.gchq.koryphe.impl.predicate.Regex or uk.gov.gchq.koryphe.impl.predicate.MultiRegex. See the Predicate examples. The predicate can then be used in you Operation View to filter out elements that don't match the regex.

When the query is run and a seed matches an edge vertex, your seed may match the source or the destination vertex. So, you need to tell the filter to apply to the opposite end of the edge. If you are running against a store that implements the MATCHED_VERTEX trait (e.g Accumulo) then it is easy. The edges returned from the store will have a matchedVertex field so you know which end of the edge your seed matched. This means you can select the vertex at the other end of the edge using the keyword ADJACENT_MATCHED_VERTEX. For example:

GetElements results = new GetElements.Builder()
    .input(new EntitySeed("X"))
    .view(new View.Builder()
        .edge("yourEdge", new ViewElementDefinition.Builder()
            .preAggregationFilter(
                new ElementFilter.Builder()
                    .select(IdentifierType.ADJACENT_MATCHED_VERTEX.name())
                    .execute(new Regex("[yY]"))
                    .build())
            .build())
        .build())
    .build();

Without the matchedVertex field it is a bit more difficult. If you are using directed edges and you know what you seed will always match the source then you can select the 'DESTINATION' in the filter.

Otherwise, you will need to provide a filter that checks the SOURCE or the DESTINATION matches the regex. For example:

GetElements results = new GetElements.Builder()
    .input(new EntitySeed("X"))
    .view(new View.Builder()
        .edge("yourEdge", new ViewElementDefinition.Builder()
            .preAggregationFilter(
                new ElementFilter.Builder()
                    .select(IdentifierType.SOURCE.name(), IdentifierType.DESTINATION.name())
                    .execute(new Or.Builder<>()
                            .select(0)
                            .execute(new Regex("[yY]"))
                            .select(1)
                            .execute(new Regex("[yY]"))
                            .build())
                    .build())
            .build())
        .build())
    .build();

For more information on filtering see: Filtering.

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