закладки (спрятать)1868
- @Repository public interface PostRepository extends BaseJpaRepository<Post, Long> { @Query(""" select p from Post p where date(p.createdOn) >= :sinceDate """ ) @QueryHints( @QueryHint(name = AvailableHints.HINT_FETCH_SIZE, value = "25") ) Stream<Post> streamByCreatedOnSince(@Param("sinceDate") LocalDate sinceDate); } The FETCH_SIZE JPA query hint is necessary for PostgreSQL and MySQL to instruct the JDBC Driver to prefetch at most 25 records. Otherwise, the PostgreSQL and MySQL JDBC Drivers would prefetch all the query results prior to traversing the underlying ResultSet.
- ["slug" being an entity attribute] Spring Data offers an existsBy query method, which we can define in the PostRepository, as follows: 1 2 3 4 5 6 @Repository public interface PostRepository extends JpaRepository<Post, Long> { boolean existsBySlug(String slug); } [another] option to emulate existence is using a CASE WHEN EXISTS native SQL query: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 @Repository public interface PostRepository extends JpaRepository<Post, Long> { @Query(value = """ SELECT CASE WHEN EXISTS ( SELECT 1 FROM post WHERE slug = :slug ) THEN 'true' ELSE 'false' END """, nativeQuery = true ) boolean existsBySlugWithCase(@Param("slug") String slug); }
- A very common workflow is to index some data based on its embeddings and then given a new query embedding retrieve the most similar examples with k-Nearest Neighbor search. For example, you can imagine embedding a large collection of papers by their abstracts and then given a new paper of interest retrieve the most similar papers to it. TLDR in my experience it ~always works better to use an SVM instead of kNN, if you can afford the slight computational hit
- Inzwischen ist es 31 Monate alt und scheint kaum etwas an Energie verloren zu haben
- pgloader will keep a separate file of rejected data, but continue trying to copy good data in your database. pgloader also implements data reformatting, a typical example of that being the transformation of MySQL datestamps 0000-00-00 and 0000-00-00 00:00:00 to PostgreSQL NULL value
- A SequenceInputStream represents the logical concatenation of other input streams. It starts out with an ordered collection of input streams and reads from the first one until end of file is reached, whereupon it reads from the second one, and so on, until end of file is reached on the last of the contained input streams.
- offlineimap -u Curses.Blinkenlights
- <button class='btn' hx-get="/contacts/?page=2" hx-target="#replaceMe" hx-swap="outerHTML">
- @misc{zhang2024autocoderover, title={AutoCodeRover: Autonomous Program Improvement}, author={Yuntong Zhang and Haifeng Ruan and Zhiyu Fan and Abhik Roychoudhury}, year={2024}, eprint={2404.05427}, archivePrefix={arXiv}, primaryClass={cs.SE} }
публикации (спрятать)356
- Proceedings of the 22Nd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, стр. 49--61. New York, NY, USA, ACM, (1995)
- University of Magdeburg, Germany, Master Thesis (Diplomarbeit), (июля 2010)In German.
- Foundations and Trends® in Machine Learning, 4 (4): 267-373 (2011)
- Proceedings of the 9th ACM/IEEE-CS Joint Conference on Digital Libraries, стр. 39--48. New York, NY, USA, ACM, (2009)
- CMU/SEI-2006-TN-011. Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA, (2006)
- Information Retrieval, (2009)
- Cambridge Studies in Linguistics Cambridge University Press, (2003)
- SIGMOD Rec., 16 (3): 249--259 (декабря 1987)
- Proceedings of the 5th USENIX Conference on File and Storage Technologies, стр. 2--2. Berkeley, CA, USA, USENIX Association, (2007)
- Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse, стр. 178--186. Sofia, Bulgaria, Association for Computational Linguistics, (августа 2013)
- (2015)cite arxiv:1511.06434Comment: Under review as a conference paper at ICLR 2016.
- BTW, том P-265 из LNI, стр. 351-360. GI, (2017)
- (2022)cite arxiv:2212.09720.
- (2023)
- (2023)cite arxiv:2302.13971.
- (2021)cite arxiv:2106.09685Comment: Draft V2 includes better baselines, experiments on GLUE, and more on adapter latency.
- (2017)cite arxiv:1706.03762Comment: 15 pages, 5 figures.
- (2020)cite arxiv:2005.14165Comment: 40+32 pages.
- (2020)cite arxiv:2009.01325Comment: NeurIPS 2020.
- (2023)cite arxiv:2305.14314Comment: Extended NeurIPS submission.
