都内で働くSEの技術的なひとりごと / Technical soliloquy of System Engineer working in Tokyo

都内でサラリーマンやってます。SQL Server を中心とした (2023年からは Azure も。) マイクロソフト系(たまに、OSS系などマイクロソフト以外の技術も...)の技術的なことについて書いています。日々の仕事の中で、気になったことを技術要素関係なく気まぐれに選んでいるので記事内容は開発言語、インフラ等ばらばらです。なお、当ブログで発信、発言は私個人のものであり、所属する組織、企業、団体等とは何のかかわりもございません。ブログの内容もきちんと検証して使用してください。英語の勉強のため、英語の

目が痛くて真夜中に起きてしまった...メール見てたら SQL Server 2017 Community Technology Preview 2.0 now available だったので、少し内容を見てみた

 次回リリースの SQL Server は、『 SQL Server 2017 』となりようです。
f:id:koogucc11:20170420031151p:plain

  • グラフデータの関係を保存および分析するためのサポート機能の追加
  • resumable online index rebuild の追加、再構築操作が一時停止された場所から再開することができる
  • Adaptive Query Processing の追加

We also added support for storing and analyzing graph data relationships. This includes full CRUD support to create nodes and edges and T-SQL query language extensions to provide multi-hop navigation using join-free pattern matching. In addition, SQL Server engine integration enables querying across SQL tables and graph data. And, you can use all of your existing SQL Server tools to work with graph data.

With resumable online index rebuild, you can resume a paused index rebuild operation from where the rebuild operation was paused rather than having to restart the operation at the beginning. Additionally, this feature rebuilds indexes using only a small amount of log space. This feature will help pick up right where you left off when an index maintenance job encounters issues, or allow you to split index rebuilds across maintenance windows.

New in SQL Server 2017, we’re adding the Adaptive Query Processing family of intelligent database features. These features automatically keep database queries running as efficiently as possible without requiring additional tuning from database administrators. In addition to the previous capability to adjust batch mode memory grants, in CTP 2.0 Adaptive Query Processing adds the batch mode adaptive joins and interleaved execution capabilities. Interleaved execution will improve the performance of queries that reference multi-statement table valued functions by surfacing runtime row counts to the query optimizer. Batch mode adaptive joins enables the choice of a query’s physical join algorithm to be deferred until actual query execution, improving performance based on runtime conditions.

  • Python をデータベース内で実行できる!
  • Microsoft Machine Learning Services というもの

Another new, key feature enhancement in CTP 2.0 of SQL Server 2017 is the ability to run the Python language in-database to scale and accelerate machine learning, predictive analytics and data science scripts. The new capability, called Microsoft Machine Learning Services, enables Python scripts to be run directly within the database server, or to be embedded into T-SQL scripts, where they can be easily deployed to the database as stored procedures and easily called from SQL client applications by stored procedure call. SQL Server 2017 will also extend Python’s performance and scale by providing a selection of parallelized algorithms that accelerate data transforms, statistical tests and analytics algorithms. This functionality and the ability to run R in-database and at scale are only available on Windows Server operating system at this time.

目がまた痛くなったきたので、寝ます。

昨日更に追加注文!