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Every Friday, we’re showing you a couple of nice new tutorial-style Java 8 features, which take advantage of lambda expressions, extension methods, and other great stuff. You’ll find the source code on GitHub. Debates about the usefulness of ORM (Object-Relational Mapping) have been going on for the last decade. While many people would agree that Hibernate and JPA solve a lot of problems very well
例えば下記のように複雑な条件に基づいてレコードを抽出する場合、WHERE を使うと残念なことになります。 SELECT T.id, ( CASE WHEN /*難解極まりない条件1*/ false THEN 1 WHEN /*難解極まりない条件2*/ false THEN 2 WHEN /*難解極まりない条件3*/ false THEN 3 ELSE 0 END ) AS stat FROM tbl T WHERE ( CASE WHEN /*難解極まりない条件1*/ false THEN 1 WHEN /*難解極まりない条件2*/ false THEN 2 WHEN /*難解極まりない条件3*/ false THEN 3 ELSE 0 END ) = 2 とても保守性が低いと思います。 WHERE を無くして stat を使用してアプリケーションレイヤーで絞り込むことも出来ますが、そうす
Google Spreadsheetを使ってたら、Query Languageというのがあるということに気づいて非常に便利だったのでメモ。 Query Language Reference (Version 0.7) | Charts | Google Developers Query LanguageというのはGoogle Spreadsheetの内容をSQLっぽい文法で絞り込んだり計算したりできるもの。 例として非常に雑な例を出すと、 簡単なTODOリストをおいている Sattus, Task名, 締切が書いてある 「TODO全体」というシートに書かれている というようなシートがあるとする。 このシートから 別シートに、DOING状態になっているタスクを日付順に抜き出したい 別シートに、Due dateを超えたタスクを抜き出したい という2つのことをやりたいとすると、Query
The ongoing progress in Artificial Intelligence is constantly expanding the realms of possibility, revolutionizing industries and societies on a global scale. The release of LLMs surged by 136% in 2023 compared to 2022, and this upward trend is projected to continue in 2024. Today, 44% of organizations are experimenting with generative AI, with 10% having […] Read blog post
The ongoing progress in Artificial Intelligence is constantly expanding the realms of possibility, revolutionizing industries and societies on a global scale. The release of LLMs surged by 136% in 2023 compared to 2022, and this upward trend is projected to continue in 2024. Today, 44% of organizations are experimenting with generative AI, with 10% having […] Read blog post
2015/10/03 phpcon 2015 updated at 2016/01/13 about default_password_lifetime's default will be 0
War of the Hadoop SQL engines. And the winner is …? You may have wondered why we were quiet over the last couple of weeks? Well, we locked ourselves into the basement and did some research and a couple of projects and PoCs on Hadoop, Big Data, and distributed processing frameworks in general. We were also looking at Clickstream data and Web Analytics solutions. Over the next couple of weeks we wil
Lot of workloads exist for Big data, batch, machine learning, search, interactive SQL, Operational/user facing applicationsApache Drill fits into the interactive SQL category Analytics on Semi-Structured/Nested dataUse standard SQL to query Nested data without upfront flattening/modelingExtensions to ANSI SQL to operate on nested dataGeneric architecture for a broad variety of nested data types (e
by The Hadoop Platforms Team Low-latency SQL queries, Business Intelligence (BI), and Data Discovery on Big Data are some of the hottest topics these days in the industry with a range of solutions coming to life lately to address them as either proprietary or open-source implementations on top of Hadoop. Some of the popular ones talked about in the Big Data communities are Hive, Presto, Impala, S
SQL is one of the most widely used languages to access, analyze, and manipulate structured data. As Hadoop gains traction within enterprise data architectures across industries, the need for SQL for both structured and loosely-structured data on Hadoop is growing rapidly Apache Drill started off with the audacious goal of delivering consistent, millisecond ANSI SQL query capability across wide ran
Real-time Ingestion and Dynamic Indexing Enjoy the power of instant indexing and adaptability, perfectly suited for handling complex and evolving data structures. Real-time indexing automatically indexes all columns, including nested structures, as data is ingested, ensuring immediate query availability with no latency. The flexible data schema dynamically adapts based on the data you ingest, offe
なぜ SQL_CALC_FOUND_ROWS や LIMIT OFFSET のページングが良く無いのか ここ最近の大規模サービス関連したデータページング考です。 mysql 5.5.34 で試して記事書いてます。 bigdata テーブルは id BIGINT UNSIGNED NOT NULL AUTO_INCREMENT, PRIMARY KEY (id) なカラムがある前提です。もちろん InnoDB です。 2014年なんだからCOUNT(*)とかSQL_CALC_FOUND_ROWSとかLIMIT OFFSETのページングはやめようぜ - Togetterまとめが発端にみえるけど、わりと昔から話されてる事なんだけど、「nippondanji SQL_CALC_FOUND_ROWS」でググっても有用な情報ないし文書化されてないからしとく。 ページング処理で使われがちな機能です。 S
2020 年に起きたワークスタイルの変化とこれからについて #GameWith #TechWith - GameWith Developer Blogこの記事は GameWith Advent Calendar 21 日目の記事です。 最近、ブログ更新を怠っていた @serima です。Splatoon 2 でナワバリバトルをする日々を送っていますが、お仕事では開発マネージャーをしています。 2020 年は新型コロナウイルスの影響で世界的に働き方の変革を求められた年であり、弊社 GameWith も例外ではありませんでした。 このポストではフルリモートワークへの切り替えにおいて気をつけたことや、現在の課題と試みについて簡単に紹介できればと思います。 なお、現時点(2020 年 12 月)においての会社としての対応は全社で原則フルリモートワーク(在宅勤務)という方針を採用しています。 もとも
SQL in Java 8: ResultSet Streams. With Java 8, writing SQL will change fundamentally, no matter what API you're using. List<Schema> result = new ArrayList<>(); try (Connection c = getConnection()) { String sql = "select schema_name, is_default " + "from information_schema.schemata " + "order by schema_name"; try (PreparedStatement stmt = c.prepareStatement(sql); ResultSet rs = stmt.executeQuery())
Enterprises see embracing AI as a strategic imperative that will enable them to stay relevant in increasingly competitive markets. However, it remains difficult to quickly build these capabilities given the challenges with finding readily available talent and resources to get started rapidly on the AI journey. Cloudera recently signed a strategic collaboration agreement with Amazon […] Read blog p
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