Spring Team
Oliver Gierke

Oliver Gierke

Spring Data Project Lead

Dresden, Germany

Oliver Gierke is the lead of the Spring Data project at Pivotal, formerly known as SpringSource, and member of the JPA 2.1 expert group. He has been into developing enterprise applications and open source projects for over 8 years now. His working focus is centered around software architecture, Spring, REST and persistence technologies. He is regularly speaking at German and international conferences and the author of technology articles as well as the first book on Spring Data.
Blog Posts by Oliver Gierke

Spring Data Release Train Ingalls RC1 Released

On behalf of the Spring Data team I’d like to announce the first (and final) release candidate of Spring Data train Ingalls. The release ships over 310 issues fixed (some of them previously released with Hopper service releases). The most important new features are:

  • Upgrade to Spring 4.3(.5) as baseline - #294.
  • Support to easily expose domain events as Spring application events from aggregate roots - DATACMNS-928.
  • Support for exists projection from derived query methods - DATACMNS-875.
  • Support for Javaslang’s Option, collection and map types on repository query methods - DATACMNS-937, DATACMNS-940.
  • Added Spring Data LDAP module taking over the repository implementation of Spring LDAP.
  • Support for MongoDB aggregation operators added in latest releases - DATAMONGO-1536.
  • Stream execution now rejects invocation without surrounding transaction in JPA - DATAJPA-1023.
  • Support for annotation based indexing and expirations in Gemfire - SGF-106, SGF-516.
  • Support for CORS configuration in Spring Data REST - DATAREST-573.
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First milestone of next-generation Spring Data released

On behalf of the Spring Data team, I’d like to announce the first milestone of the Kay release train. This is a special release train as it’s going to ship a new generation of Spring Data that will include a couple of breaking changes going forward.

Infrastructure upgrades

The first and most noticeable change is the upgrade to Java 8 as a minimum baseline (no JDK 6 compatibility anymore) and an upgrade to Spring 5 as framework foundation. In subsequent milestones we’re going to ship some significant internal rewrites that will also affect user facing API to make use of the new language features in JDK 8.

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Spring Data release train Hopper SR5 released

On behalf of the Spring Data team I am happy to announce the fifth service release of Spring Data Hopper. It contains variety of bug fixes and is a recommended upgrade for all users of this or any previous release train. The overall list of fixed tickets can be found here.

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Spring Data Hopper SR4 and Gosling SR6 released

On behalf of the entire team I’d like to announce the availability of two service releases for Spring Data release trains: Hopper SR4 and Gosling SR6. The releases are recommended upgrades as they contain fixes for a CVE in Spring Data JPA.

Spring Boot 1.3.8 and 1.4.1 users got Hopper SR3 and Gosling SR5 shipped out of the box. Those releases also already contain the fixes for CVE but unfortunately broke Java 6 compatibility. To re-instantiate the latter, please upgrade to the latest ones by setting the spring-data-releasetrain.version property to the corresponding value. Non-Boot users can just upgrade to the new BOM. As usual, the next Spring Boot releases will pick up the improved fixes as part of their dependency upgrades.

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Spring Data Release Train Hopper Goes GA (and SR1)!

On behalf of the entire Spring Data team I am happy to announce the general availability of the Spring Data release train Hopper. The train includes 395 tickets fixed and its most important additions are:

  • Upgrade of the Spring Framework baseline to 4.2 (4.2.5 in particular).
  • Support for Query by Example in Spring Data JPA and MongoDB.
  • Improved support for composed annotations.
  • Support for lookup types and nested associations in Spring Data REST
  • Major upgrades of the Solr (2.0 on Solr 5.5), Neo4j (4.1), Couchbase (2.1 on Couchbase 2.0), Elasticsearch (2.0 on ES 2.2)
  • Upgrade to Querydsl 4.
  • Support for object mapping and repositories for Spring Data Redis.
  • Support for Redis Cluster.
  • Support for projections on repository query methods in JPA and MongoDB.
  • Addition of Spring Data Envers to the release train (previously maintained separately).
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First Release Candidate of Spring Data Hopper Released

In behalf of the Spring Data team I am happy to announce the first and final release candidate for the Hopper release train. The release ships with a couple of important changes and updates:

  • Upgrade of the Spring Framework baseline to 4.2 (4.2.5 in particular).
  • Support for Query by Example in Spring Data JPA and MongoDB.
  • Support for object mapping and repositories for Spring Data Redis.
  • Improved support for composed annotations.
  • Support for lookup types and nested associations in Spring Data REST
  • Upgrade to Elasticsearch 2.2, and thus the version number change of Spring Data Elasticsearch to 2.0
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Spring Data Gosling SR4 released

In preparation of a Spring Boot service release on the horizon, I am pleased to announce the fourth service release of the Spring Data release train Gosling. As usual, service releases contain bugfixes — 45 in total this time —, so that an upgrade is highly recommended.

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Spring Data Release Train Hopper M1 Released

On behalf of the Spring Data team I’m happy to announce the first milestone of the Hopper release train. The release ships 250 tickets fixed! The most important new features are:

  • Upgrade to Querydsl 4.
  • Integration of Spring Data Neo4j 4.1, Spring Data Couchbase 2.1 and Spring Data Solr 2 (on Solr 5).
  • Support for Redis Cluster.
  • Support for projections on repository query methods in JPA and MongoDB (see the example for details).
  • Addition of Spring Data Envers to the release train (previously maintained separately).
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Spring Data release train Gosling SR2 released

On behalf of the Spring Data team I’d like to announce the availability of the second service release of the Spring Data Gosling release train. The release ships 45 issues fixed and contains an important bugfix for an issue in Spring Data JPA’s method metadata detection. Thus it’s a recommended upgrade for all Gosling users and also users of previous release trains.

The release is be included in the just released Spring Boot 1.3.1 release which should make the upgrade a non-issue. If you’re using the BOM, make sure you upgrade to Gosling-SR2A (note the trailing A). A tiny glitch during the release forced us into that slightly weird version number.

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Spring Data Release Train Gosling Goes GA

On behalf of the Spring Data team I’d like to announce the general availability of the Spring Data release train Gosling. Over the last 6 months we’ve fixed 344 tickets in total, 56 of that after the latest release candidate.

  • Upgraded Spring baseline to 4.1.
  • Easier implementability of custom repository code (per repo, see the reference documentation) .
  • Improved compatibility with Hibernate 5 (JPA module).
  • SpEl support for @Query methods in MongoDB (see this example).
  • Support to create Querydsl Predicates from web requests (see the reference documentation).
  • A new Spring Data KeyValue module for Map-backed repositories using SpEL as query language.
  • Improved POST forms for the HAL browser in Spring Data REST.
  • Support for internationalization of enum values and link titles in Spring Data REST.
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