ブログでもいろいろ解説しています。
http://little-hands.hatenablog.com/entry/top
ドメイン駆動設計屈指の難解な概念「境界付けられたコンテキスト」について解説します。
---
公式DDD Referenceの定義は以下の通りです。(和訳はだいぶ意訳しています)
bounded context
A description of a boundary (typically a subsystem, or the work of a particular team) within which a particular model is defined and applicable.
境界付けられたコンテキスト
特定のモデルを定義・適用する境界を明示的に示したもの。
代表的な境界の例は、サブシステムやチームなど。
まぁなかなかよくわからないですよね。DDD用語の中でもかなり難解なワードです。 境界付けられたコンテキストは、2つの観点から解説が必要でしょう。
・概念としての境界付けられたコンテキスト
・境界付けられたコンテキストをどう実装に落としこむか
今回のスライドでは、概念の方の説明をしたいと思います。
ブログでもいろいろ解説しています。
http://little-hands.hatenablog.com/entry/top
ドメイン駆動設計屈指の難解な概念「境界付けられたコンテキスト」について解説します。
---
公式DDD Referenceの定義は以下の通りです。(和訳はだいぶ意訳しています)
bounded context
A description of a boundary (typically a subsystem, or the work of a particular team) within which a particular model is defined and applicable.
境界付けられたコンテキスト
特定のモデルを定義・適用する境界を明示的に示したもの。
代表的な境界の例は、サブシステムやチームなど。
まぁなかなかよくわからないですよね。DDD用語の中でもかなり難解なワードです。 境界付けられたコンテキストは、2つの観点から解説が必要でしょう。
・概念としての境界付けられたコンテキスト
・境界付けられたコンテキストをどう実装に落としこむか
今回のスライドでは、概念の方の説明をしたいと思います。
2020年12月2日(水)15時30分-16時10分
db tech showcase ONLINE 2020 Japan Oracle User Group (JPOUG) SPECIAL SESSION
Oracle Databaseバージョン選択おける考察’20 諸橋 渉
"2010年から2020年までの10年におけるリリースモデルの変遷とサポートライフサイクルの変遷を振り返ります。そして同観点での AWSとOracle CloudにおけるOracle Database as a Serviceの動向を把握します。 これらを踏まえた上で、バージョン選定と採用時期を決めるための考察をお話します。"
ビデオ・アーカイブ https://youtu.be/n50AtiKHBEk
29回勉強会資料「PostgreSQLのリカバリ超入門」
See also http://www.interdb.jp/pgsql (Coming soon!)
初心者向け。PostgreSQLのWAL、CHECKPOINT、 オンラインバックアップの仕組み解説。
これを見たら、次は→ http://www.slideshare.net/satock/29shikumi-backup
In the first half, we give an introduction to modern serialization systems, Protocol Buffers, Apache Thrift and Apache Avro. Which one does meet your needs?
In the second half, we show an example of data ingestion system architecture using Apache Avro.
This document contains links to MongoDB documentation pages about sharding, databases, collections, inserting, querying, updating, indexing, replication, and backups. It includes a link to a slideshare presentation on MongoDB sharding and links to pages explaining replica set internals and operations.
2020年12月2日(水)15時30分-16時10分
db tech showcase ONLINE 2020 Japan Oracle User Group (JPOUG) SPECIAL SESSION
Oracle Databaseバージョン選択おける考察’20 諸橋 渉
"2010年から2020年までの10年におけるリリースモデルの変遷とサポートライフサイクルの変遷を振り返ります。そして同観点での AWSとOracle CloudにおけるOracle Database as a Serviceの動向を把握します。 これらを踏まえた上で、バージョン選定と採用時期を決めるための考察をお話します。"
ビデオ・アーカイブ https://youtu.be/n50AtiKHBEk
29回勉強会資料「PostgreSQLのリカバリ超入門」
See also http://www.interdb.jp/pgsql (Coming soon!)
初心者向け。PostgreSQLのWAL、CHECKPOINT、 オンラインバックアップの仕組み解説。
これを見たら、次は→ http://www.slideshare.net/satock/29shikumi-backup
In the first half, we give an introduction to modern serialization systems, Protocol Buffers, Apache Thrift and Apache Avro. Which one does meet your needs?
In the second half, we show an example of data ingestion system architecture using Apache Avro.
This document contains links to MongoDB documentation pages about sharding, databases, collections, inserting, querying, updating, indexing, replication, and backups. It includes a link to a slideshare presentation on MongoDB sharding and links to pages explaining replica set internals and operations.
The document provides tips and explanations for various MongoDB commands and operations including explain, hint, setProfilingLevel, currentOp, and mongostat. It discusses using indexes to optimize queries, setting profiling levels to log slow queries, using currentOp to view currently running operations, and using mongostat to view MongoDB server statistics.
This document discusses MongoDB and replica sets. It provides an overview of MongoDB's features and benefits including scalability, high availability, and flexibility in schema design. It also explains how replica sets work, including generating the set, initializing replicas, handling failures, failover, and recovery. Replica sets allow for continuous availability and redundancy of data.
This document discusses recent developments in the cloud computing market. It analyzes strategies and acquisitions by major players like Amazon, Microsoft, Google, IBM, Oracle, and others. It attempts to categorize cloud services into infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). The structure of the cloud computing market has evolved from a single public cloud to a mix of public, private, and hybrid cloud models. The document predicts corporations will increasingly utilize a mix of public and private clouds to meet different application and data needs.
MongoDB's indexes are B-Trees.
Lookups (queries), inserts and deletes happen in O(log(n)) time.
TODO: Add a page describing what a B-Tree is???
So this is helpful, and can speed up queries by a tremendous amount
unique applies a uniqueness constant on duplicate values.
dropDups will force the server to create a unique index by only keeping the first document found in natural order with a value and dropping all other documents with that value.
dropDups will likely result in data loss!!! Make sure you know what it does before you use it.
MongoDB doesn't enforce a schema – documents are not required to have the same fields.
Sparse indexes only contain entries for documents that have the indexed field.
Without sparse, documents without field 'a' have a null entry in the index for that field.
With sparse a unique constraint can be applied to a field not shared by all documents. Otherwise multiple 'null' values violate the unique constraint.
cursor – the type of cursor used. BasicCursor means no index was used. TODO: Use a real example here instead of made up numbers…
n – the number of documents that match the query
nscannedObjects – the number of documents that had to be scanned
nscanned – the number of items (index entries or documents) examined
millis – how long the query took
Ratio of n to nscanned should be as close to 1 as possible.
cursor – the type of cursor used. BasicCursor means no index was used. TODO: Use a real example here instead of made up numbers…
n – the number of documents that match the query
nscannedObjects – the number of documents that had to be scanned
nscanned – the number of items (index entries or documents) examined
millis – how long the query took
Ratio of n to nscanned should be as close to 1 as possible.
Indexes should be contained in working set.
From mainframes, to RAC Oracle servers... People solved problems by adding more resources to a single machine.
Large scale operation can be combined with high performance on commodity hardware through horizontal scaling
Build
- Document oriented database maps perfectly to object oriented languages
Scale
- MongoDB presents clear path to scalability that isn't ops intensive
- Provides same interface for sharded cluster as single instance