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Chapter 2. Creating Ickle queries


Data Grid provides an Ickle query language that lets you create relational and full-text queries.

2.1. Ickle queries

To use the API, first obtain a QueryFactory to the cache and then call the .create() method, passing in the string to use in the query. Each QueryFactory instance is bound to the same Cache instance as the Search, but it is otherwise a stateless and thread-safe object that can be used for creating multiple queries in parallel.

For instance:

// Remote Query, using protobuf
QueryFactory qf = org.infinispan.client.hotrod.Search.getQueryFactory(remoteCache);
Query<Transaction> q = qf.create("from sample_bank_account.Transaction where amount > 20");

// Embedded Query using Java Objects
QueryFactory qf = org.infinispan.query.Search.getQueryFactory(cache);
Query<Transaction> q = qf.create("from org.infinispan.sample.Book where price > 20");

// Execute the query
QueryResult<Book> queryResult = q.execute();
Note

A query will always target a single entity type and is evaluated over the contents of a single cache. Running a query over multiple caches or creating queries that target several entity types (joins) is not supported.

Executing the query and fetching the results is as simple as invoking the execute() method of the Query object. Once executed, calling execute() on the same instance will re-execute the query.

2.1.1. Pagination

You can limit the number of returned results by using the Query.maxResults(int maxResults). This can be used in conjunction with Query.startOffset(long startOffset) to achieve pagination of the result set.

// sorted by year and match all books that have "clustering" in their title
// and return the third page of 10 results
Query<Book> query = queryFactory.create("FROM org.infinispan.sample.Book WHERE title like '%clustering%' ORDER BY year").startOffset(20).maxResults(10)
Note

If you don’t explicitly set the maxResults for a query instance, Data Grid limits the number of results returned by the query to 100. You can change the default limit by setting the query.default-max-results cache property.

2.1.2. Number of hits

The QueryResult object includes the .hitCount() method, which returns a hit count value that represents the total number of results from a query, regardless of any pagination parameter. The hit count is only available for indexed queries for performance reasons.

2.1.2.1. Hit count accuracy

To optimize performance, the default accuracy of the hit count is set to 10000. You can limit the required accuracy of hit counts by setting query.hit-count-accuracy cache property. Alternatively, you can set the limit on each query instance.

When the hit count exceeds the specified limit, Data Grid does not return any value for the hit count. When using the HotRod client or embedded query API, Data Grid returns null, and when using the REST query API, Data Grid respons with -1L. While setting the hit count accuracy to Integer.MAX would return accurate results for any query, it would negatively impact query performance.

For optimal performance, set the property value slightly above the expected hit count. If you do not require precise hit counts, set it to a low value.

2.1.3. Iteration

The Query object has the .iterator() method to obtain the results lazily. It returns an instance of CloseableIterator that must be closed after usage.

Note

The iteration support for Remote Queries is currently limited, as it will first fetch all entries to the client before iterating.

2.1.4. Named query parameters

Instead of building a new Query object for every execution it is possible to include named parameters in the query which can be substituted with actual values before execution. This allows a query to be defined once and be efficiently executed many times. Parameters can only be used on the right-hand side of an operator and are defined when the query is created by supplying an object produced by the org.infinispan.query.dsl.Expression.param(String paramName) method to the operator instead of the usual constant value. Once the parameters have been defined they can be set by invoking either Query.setParameter(parameterName, value) or Query.setParameters(parameterMap) as shown in the examples below. ⁠

QueryFactory queryFactory = Search.getQueryFactory(cache);
// Defining a query to search for various authors and publication years
Query<Book> query = queryFactory.create("SELECT title FROM org.infinispan.sample.Book WHERE author = :authorName AND publicationYear = :publicationYear").build();

// Set actual parameter values
query.setParameter("authorName", "Doe");
query.setParameter("publicationYear", 2010);

// Execute the query
List<Book> found = query.execute().list();

Alternatively, you can supply a map of actual parameter values to set multiple parameters at once: ⁠

Setting multiple named parameters at once

Map<String, Object> parameterMap = new HashMap<>();
parameterMap.put("authorName", "Doe");
parameterMap.put("publicationYear", 2010);

query.setParameters(parameterMap);

Note

A significant portion of the query parsing, validation and execution planning effort is performed during the first execution of a query with parameters. This effort is not repeated during subsequent executions leading to better performance compared to a similar query using constant values instead of query parameters.

2.1.5. Query execution

The Query API provides two methods for executing Ickle queries on a cache:

  • Query.execute() runs a SELECT statement and returns a result.
  • Query.executeStatement() runs a DELETE statement and modifies data.
Note

You should always invoke executeStatement() to modify data and invoke execute() to get the result of a query.

2.2. Ickle query language syntax

The Ickle query language is subset of the JPQL query language, with some extensions for full-text.

The parser syntax has some notable rules:

  • Whitespace is not significant.
  • Wildcards are not supported in field names.
  • A field name or path must always be specified, as there is no default field.
  • && and || are accepted instead of AND or OR in both full-text and JPA predicates.
  • ! may be used instead of NOT.
  • A missing boolean operator is interpreted as OR.
  • String terms must be enclosed with either single or double quotes.
  • Fuzziness and boosting are not accepted in arbitrary order; fuzziness always comes first.
  • != is accepted instead of <>.
  • Boosting cannot be applied to >,>=,<,<= operators. Ranges may be used to achieve the same result.

2.2.1. Filtering operators

Ickle support many filtering operators that can be used for both indexed and non-indexed fields.

OperatorDescriptionExample

in

Checks that the left operand is equal to one of the elements from the Collection of values given as argument.

FROM Book WHERE isbn IN ('ZZ', 'X1234')

like

Checks that the left argument (which is expected to be a String) matches a wildcard pattern that follows the JPA rules.

FROM Book WHERE title LIKE '%Java%'

=

Checks that the left argument is an exact match of the given value.

FROM Book WHERE name = 'Programming Java'

!=

Checks that the left argument is different from the given value.

FROM Book WHERE language != 'English'

>

Checks that the left argument is greater than the given value.

FROM Book WHERE price > 20

>=

Checks that the left argument is greater than or equal to the given value.

FROM Book WHERE price >= 20

<

Checks that the left argument is less than the given value.

FROM Book WHERE year < 2020

<=

Checks that the left argument is less than or equal to the given value.

FROM Book WHERE price ⇐ 50

between

Checks that the left argument is between the given range limits.

FROM Book WHERE price BETWEEN 50 AND 100

2.2.2. Boolean conditions

Combining multiple attribute conditions with logical conjunction (and) and disjunction (or) operators in order to create more complex conditions is demonstrated in the following example. The well known operator precedence rule for boolean operators applies here, so the order of the operators is irrelevant. Here and operator still has higher priority than or even though or was invoked first.

# match all books that have "Data Grid" in their title
# or have an author named "Manik" and their description contains "clustering"

FROM org.infinispan.sample.Book WHERE title LIKE '%Data Grid%' OR author.name = 'Manik' AND description like '%clustering%'

Boolean negation has highest precedence among logical operators and applies only to the next simple attribute condition.

# match all books that do not have "Data Grid" in their title and are authored by "Manik"
FROM org.infinispan.sample.Book WHERE title != 'Data Grid' AND author.name = 'Manik'

2.2.3. Nested conditions

Changing the precedence of logical operators is achieved with parenthesis:

# match all books that have an author named "Manik" and their title contains
# "Data Grid" or their description contains "clustering"
FROM org.infinispan.sample.Book WHERE author.name = 'Manik' AND ( title like '%Data Grid%' OR description like '% clustering%')

2.2.4. Projections with SELECT statements

In some use cases returning the whole domain object is overkill if only a small subset of the attributes are actually used by the application, especially if the domain entity has embedded entities. The query language allows you to specify a subset of attributes (or attribute paths) to return - the projection. If projections are used then the QueryResult.list() will not return the whole domain entity but will return a List of Object[], each slot in the array corresponding to a projected attribute.

# match all books that have "Data Grid" in their title or description
# and return only their title and publication year
SELECT title, publicationYear FROM org.infinispan.sample.Book WHERE title like '%Data Grid%' OR description like '%Data Grid%'

2.2.4.1. Project cache entry version

It is possible to project the cache entry version, using the version projection function.

# return the title, publication year and the cache entry version
SELECT b.title, b.publicationYear, version(b) FROM org.infinispan.sample.Book b WHERE b.title like '%Data Grid%'

2.2.4.2. Project cache entry value

It is possible to project the cache entry value together with other projections. It can be used for instance to project the cache entry value together with the cache entry version in the same Object[] returned hit.

# return the cache entry value and the cache entry version
SELECT b, version(b) FROM org.infinispan.sample.Book b WHERE b.title like '%Data Grid%'

Sorting

Ordering the results based on one or more attributes or attribute paths is done with the ORDER BY clause. If multiple sorting criteria are specified, then the order will dictate their precedence.

# match all books that have "Data Grid" in their title or description
# and return them sorted by the publication year and title
FROM org.infinispan.sample.Book WHERE title like '%Data Grid%' ORDER BY publicationYear DESC, title ASC

2.2.5. Grouping and aggregation

Data Grid has the ability to group query results according to a set of grouping fields and construct aggregations of the results from each group by applying an aggregation function to the set of values that fall into each group. Grouping and aggregation can only be applied to projection queries (queries with one or more field in the SELECT clause).

The supported aggregations are: avg, sum, count, max, and min.

The set of grouping fields is specified with the GROUP BY clause and the order used for defining grouping fields is not relevant. All fields selected in the projection must either be grouping fields or else they must be aggregated using one of the grouping functions described below. A projection field can be aggregated and used for grouping at the same time. A query that selects only grouping fields but no aggregation fields is legal. ⁠ Example: Grouping Books by author and counting them.

SELECT author, COUNT(title) FROM org.infinispan.sample.Book WHERE title LIKE '%engine%' GROUP BY author
Note

A projection query in which all selected fields have an aggregation function applied and no fields are used for grouping is allowed. In this case the aggregations will be computed globally as if there was a single global group.

Aggregations

You can apply the following aggregation functions to a field:

Table 2.1. Index merge attributes
Aggregation functionDescription

avg()

Computes the average of a set of numbers. Accepted values are primitive numbers and instances of java.lang.Number. The result is represented as java.lang.Double. If there are no non-null values the result is null instead.

count()

Counts the number of non-null rows and returns a java.lang.Long. If there are no non-null values the result is 0 instead.

max()

Returns the greatest value found. Accepted values must be instances of java.lang.Comparable. If there are no non-null values the result is null instead.

min()

Returns the smallest value found. Accepted values must be instances of java.lang.Comparable. If there are no non-null values the result is null instead.

sum()

Computes the sum of a set of Numbers. If there are no non-null values the result is null instead. The following table indicates the return type based on the specified field.

Table 2.2. Table sum return type
Field TypeReturn Type

Integral (other than BigInteger)

Long

Float or Double

Double

BigInteger

BigInteger

BigDecimal

BigDecimal

Evaluation of queries with grouping and aggregation

Aggregation queries can include filtering conditions, like usual queries. Filtering can be performed in two stages: before and after the grouping operation. All filter conditions defined before invoking the groupBy() method will be applied before the grouping operation is performed, directly to the cache entries (not to the final projection). These filter conditions can reference any fields of the queried entity type, and are meant to restrict the data set that is going to be the input for the grouping stage. All filter conditions defined after invoking the groupBy() method will be applied to the projection that results from the projection and grouping operation. These filter conditions can either reference any of the groupBy() fields or aggregated fields. Referencing aggregated fields that are not specified in the select clause is allowed; however, referencing non-aggregated and non-grouping fields is forbidden. Filtering in this phase will reduce the amount of groups based on their properties. Sorting can also be specified similar to usual queries. The ordering operation is performed after the grouping operation and can reference any of the groupBy() fields or aggregated fields.

2.2.6. DELETE statements

You can delete entities from Data Grid caches with the following syntax:

DELETE FROM <entityName> [WHERE condition]
  • Reference only single entities with <entityName>. DELETE queries cannot use joins.
  • WHERE conditions are optional.

DELETE queries cannot use any of the following:

  • Projections with SELECT statements
  • Grouping and aggregation
  • ORDER BY clauses
Tip

Invoke the Query.executeStatement() method to execute DELETE statements.

2.3. Full-text queries

You can perform full-text searches with the Ickle query language.

2.3.1. Fuzzy queries

To execute a fuzzy query add ~ along with an integer, representing the distance from the term used, after the term. For instance

FROM sample_bank_account.Transaction WHERE description : 'cofee'~2

2.3.2. Range queries

To execute a range query define the given boundaries within a pair of braces, as seen in the following example:

FROM sample_bank_account.Transaction WHERE amount : [20 to 50]

2.3.3. Phrase queries

A group of words can be searched by surrounding them in quotation marks, as seen in the following example:

FROM sample_bank_account.Transaction WHERE description : 'bus fare'

2.3.4. Proximity queries

To execute a proximity query, finding two terms within a specific distance, add a ~ along with the distance after the phrase. For instance, the following example will find the words canceling and fee provided they are not more than 3 words apart:

FROM sample_bank_account.Transaction WHERE description : 'canceling fee'~3

2.3.5. Wildcard queries

To search for "text" or "test", use the ? single-character wildcard search:

FROM sample_bank_account.Transaction where description : 'te?t'

To search for "test", "tests", or "tester", use the * multi-character wildcard search:

FROM sample_bank_account.Transaction where description : 'test*'

2.3.6. Regular expression queries

Regular expression queries can be performed by specifying a pattern between /. Ickle uses Lucene’s regular expression syntax, so to search for the words moat or boat the following could be used:

FROM sample_library.Book  where title : /[mb]oat/

2.3.7. Boosting queries

Terms can be boosted by adding a ^ after the term to increase their relevance in a given query, the higher the boost factor the more relevant the term will be. For instance to search for titles containing beer and wine with a higher relevance on beer, by a factor of 3, the following could be used:

FROM sample_library.Book WHERE title : beer^3 OR wine
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