1.1. Technical Overview1.1.1. Docum

1.1. Technical Overview
1.1.1. Document Storage
A CouchDB server hosts named databases, which store documents. Each document is uniquely named in the database, and CouchDB provides aRESTful HTTP API for reading and updating (add, edit, delete) database documents.
Documents are the primary unit of data in CouchDB and consist of any number of fields and attachments. Documents also include metadata that’s maintained by the database system. Document fields are uniquely named and contain values of varying types (text, number, boolean, lists, etc), and there is no set limit to text size or element count.
The CouchDB document update model is lockless and optimistic. Document edits are made by client applications loading documents, applying changes, and saving them back to the database. If another client editing the same document saves their changes first, the client gets an edit conflict error on save. To resolve the update conflict, the latest document version can be opened, the edits reapplied and the update tried again.
Document updates (add, edit, delete) are all or nothing, either succeeding entirely or failing completely. The database never contains partially saved or edited documents.
1.1.2. ACID Properties
The CouchDB file layout and commitment system features all Atomic Consistent Isolated Durable (ACID) properties. On-disk, CouchDB never overwrites committed data or associated structures, ensuring the database file is always in a consistent state. This is a “crash-only” design where the CouchDB server does not go through a shut down process, it’s simply terminated.
Document updates (add, edit, delete) are serialized, except for binary blobs which are written concurrently. Database readers are never locked out and never have to wait on writers or other readers. Any number of clients can be reading documents without being locked out or interrupted by concurrent updates, even on the same document. CouchDB read operations use a Multi-Version Concurrency Control (MVCC) model where each client sees a consistent snapshot of the database from the beginning to the end of the read operation.
Documents are indexed in B-trees by their name (DocID) and a Sequence ID. Each update to a database instance generates a new sequential number. Sequence IDs are used later for incrementally finding changes in a database. These B-tree indexes are updated simultaneously when documents are saved or deleted. The index updates always occur at the end of the file (append-only updates).
Documents have the advantage of data being already conveniently packaged for storage rather than split out across numerous tables and rows in most database systems. When documents are committed to disk, the document fields and metadata are packed into buffers, sequentially one document after another (helpful later for efficient building of views).
When CouchDB documents are updated, all data and associated indexes are flushed to disk and the transactional commit always leaves the database in a completely consistent state. Commits occur in two steps:
1. All document data and associated index updates are synchronously flushed to disk.
2. The updated database header is written in two consecutive, identical chunks to make up the first 4k of the file, and then synchronously flushed to disk.
In the event of an OS crash or power failure during step 1, the partially flushed updates are simply forgotten on restart. If such a crash happens during step 2 (committing the header), a surviving copy of the previous identical headers will remain, ensuring coherency of all previously committed data. Excepting the header area, consistency checks or fix-ups after a crash or a power failure are never necessary.
1.1.3. Compaction
Wasted space is recovered by occasional compaction. On schedule, or when the database file exceeds a certain amount of wasted space, the compaction process clones all the active data to a new file and then discards the old file. The database remains completely online the entire time and all updates and reads are allowed to complete successfully. The old database file is deleted only when all the data has been copied and all users transitioned to the new file.
1.1.4. Views
ACID properties only deal with storage and updates, but we also need the ability to show our data in interesting and useful ways. Unlike SQL databases where data must be carefully decomposed into tables, data in CouchDB is stored in semi-structured documents. CouchDB documents are flexible and each has its own implicit structure, which alleviates the most difficult problems and pitfalls of bi-directionally replicating table schemas and their contained data.
But beyond acting as a fancy file server, a simple document model for data storage and sharing is too simple to build real applications on – it simply doesn’t do enough of the things we want and expect. We want to slice and dice and see our data in many different ways. What is needed is a way to filter, organize and report on data that hasn’t been decomposed into tables.
See also
Guide to Views
View Model
To address this problem of adding structure back to unstructured and semi-structured data, CouchDB integrates a view model. Views are the method of aggregating and reporting on the documents in a database, and are built on-demand to aggregate, join and report on database documents. Because views are built dynamically and don’t affect the underlying document, you can have as many different view representations of the same data as you like.
View definitions are strictly virtual and only display the documents from the current database instance, making them separate from the data they display and compatible with replication. CouchDB views are defined inside special design documents and can replicate across database instances like regular documents, so that not only data replicates in CouchDB, but entire application designs replicate too.
Javascript View Functions
Views are defined using Javascript functions acting as the map part in a map-reduce system. A view function takes a CouchDB document as an argument and then does whatever computation it needs to do to determine the data that is to be made available through the view, if any. It can add multiple rows to the view based on a single document, or it can add no rows at all.
See also
View functions
View Indexes
Views are a dynamic representation of the actual document contents of a database, and CouchDB makes it easy to create useful views of data. But generating a view of a database with hundreds of thousands or millions of documents is time and resource consuming, it’s not something the system should do from scratch each time.
To keep view querying fast, the view engine maintains indexes of its views, and incrementally updates them to reflect changes in the database. CouchDB’s core design is largely optimized around the need for efficient, incremental creation of views and their indexes.
Views and their functions are defined inside special “design” documents, and a design document may contain any number of uniquely named view functions. When a user opens a view and its index is automatically updated, all the views in the same design document are indexed as a single group.
The view builder uses the database sequence ID to determine if the view group is fully up-to-date with the database. If not, the view engine examines the all database documents (in packed sequential order) changed since the last refresh. Documents are read in the order they occur in the disk file, reducing the frequency and cost of disk head seeks.
The views can be read and queried simultaneously while also being refreshed. If a client is slowly streaming out the contents of a large view, the same view can be concurrently opened and refreshed for another client without blocking the first client. This is true for any number of simultaneous client readers, who can read and query the view while the index is concurrently being refreshed for other clients without causing problems for the readers.
As documents are processed by the view engine through your ‘map’ and ‘reduce’ functions, their previous row values are removed from the view indexes, if they exist. If the document is selected by a view function, the function results are inserted into the view as a new row.
When view index changes are written to disk, the updates are always appended at the end of the file, serving to both reduce disk head seek times during disk commits and to ensure crashes and power failures can not cause corruption of indexes. If a crash occurs while updating a view index, the incomplete index updates are simply lost and rebuilt incrementally from its previously committed state
1.1.5. Security and Validation
To protect who can read and update documents, CouchDB has a simple reader access and update validation model that can be extended to implement custom security models.
See also
/db/_security
Administrator Access
CouchDB database instances have administrator accounts. Administrator accounts can create other administrator accounts and update design documents. Design documents are special documents containing view definitions and other special formulas, as well as regular fields and blobs.
Update Validation
As documents written to disk, they can be validated dynamically by javascript functions for both security and data validation. When the document passes all the formula validation criteria, the update is allowed to continue. If the validation fails, the update is aborted and the user client gets an error response.
Both the user’s credentials and the updated document are given as inputs to the validation formula, and can be used to implement custom security models by validating a user’s permissions to update a document.
A basic “author only” update document model is trivial to implement, where document updates are validated to check if the user is listed in an “author” field in the existing document. More dynamic

ผลลัพธ์ (ไทย) 1:

1.1. เทคนิคภาพรวม1.1.1 เก็บเอกสารโฮสต์เซิร์ฟเวอร์ CouchDB ชื่อฐานข้อมูล การจัดเก็บเอกสาร ฐานข้อมูลเฉพาะชื่อเอกสารแต่ละ และ CouchDB ให้ aRESTful HTTP API สำหรับการอ่าน และปรับปรุง (เพิ่ม แก้ไข ลบ) ฐานข้อมูลเอกสารเอกสารเป็นหน่วยหลักของข้อมูลใน CouchDB และประกอบด้วยหมายเลขของฟิลด์สิ่งที่แนบมา เอกสารยังประกอบด้วยข้อมูลเมตาที่ถูกเก็บรักษา โดยระบบฐานข้อมูล เขตข้อมูลเอกสารโดยเฉพาะการตั้งชื่อ และประกอบด้วยค่าของชนิดที่แตกต่างกัน (ข้อความ หมายเลข บูลีน รายชื่อ ฯลฯ), และมีข้อจำกัดการตั้งค่าจำนวนขนาดหรือองค์ประกอบของข้อความแบบจำลองการปรับปรุงเอกสาร CouchDB จะ lockless และในเชิงบวก แอพลิเคชันไคลเอนต์โหลดเอกสาร ใช้การเปลี่ยนแปลง และบันทึกกลับไปยังฐานข้อมูลการแก้ไขเอกสาร ถ้าไคลเอนต์อื่นที่แก้ไขเอกสารเดียวกันบันทึกการเปลี่ยนแปลงครั้งแรก ได้รับการไคลเอ็นต์ที่การแก้ไขความขัดแย้งข้อผิดพลาดในบันทึก การขัด การปรับปรุงเอกสารรุ่นล่าสุดสามารถเปิด แก้ไขการแสดงและการปรับปรุงที่พยายามอีกครั้งเอกสารปรับปรุง (เพิ่ม แก้ไข ลบ) มีทั้งหมดหรือไม่ โปรแกรมทั้งหมด หรือล้มเหลวอย่างสมบูรณ์ ฐานข้อมูลไม่เคยประกอบด้วยบันทึกไว้บางส่วน หรือแก้ไขเอกสาร1.1.2 คุณสมบัติกรดThe CouchDB file layout and commitment system features all Atomic Consistent Isolated Durable (ACID) properties. On-disk, CouchDB never overwrites committed data or associated structures, ensuring the database file is always in a consistent state. This is a “crash-only” design where the CouchDB server does not go through a shut down process, it’s simply terminated.Document updates (add, edit, delete) are serialized, except for binary blobs which are written concurrently. Database readers are never locked out and never have to wait on writers or other readers. Any number of clients can be reading documents without being locked out or interrupted by concurrent updates, even on the same document. CouchDB read operations use a Multi-Version Concurrency Control (MVCC) model where each client sees a consistent snapshot of the database from the beginning to the end of the read operation.Documents are indexed in B-trees by their name (DocID) and a Sequence ID. Each update to a database instance generates a new sequential number. Sequence IDs are used later for incrementally finding changes in a database. These B-tree indexes are updated simultaneously when documents are saved or deleted. The index updates always occur at the end of the file (append-only updates).Documents have the advantage of data being already conveniently packaged for storage rather than split out across numerous tables and rows in most database systems. When documents are committed to disk, the document fields and metadata are packed into buffers, sequentially one document after another (helpful later for efficient building of views).When CouchDB documents are updated, all data and associated indexes are flushed to disk and the transactional commit always leaves the database in a completely consistent state. Commits occur in two steps:1. All document data and associated index updates are synchronously flushed to disk.2. The updated database header is written in two consecutive, identical chunks to make up the first 4k of the file, and then synchronously flushed to disk.In the event of an OS crash or power failure during step 1, the partially flushed updates are simply forgotten on restart. If such a crash happens during step 2 (committing the header), a surviving copy of the previous identical headers will remain, ensuring coherency of all previously committed data. Excepting the header area, consistency checks or fix-ups after a crash or a power failure are never necessary.1.1.3. CompactionWasted space is recovered by occasional compaction. On schedule, or when the database file exceeds a certain amount of wasted space, the compaction process clones all the active data to a new file and then discards the old file. The database remains completely online the entire time and all updates and reads are allowed to complete successfully. The old database file is deleted only when all the data has been copied and all users transitioned to the new file.1.1.4. ViewsACID properties only deal with storage and updates, but we also need the ability to show our data in interesting and useful ways. Unlike SQL databases where data must be carefully decomposed into tables, data in CouchDB is stored in semi-structured documents. CouchDB documents are flexible and each has its own implicit structure, which alleviates the most difficult problems and pitfalls of bi-directionally replicating table schemas and their contained data.But beyond acting as a fancy file server, a simple document model for data storage and sharing is too simple to build real applications on – it simply doesn’t do enough of the things we want and expect. We want to slice and dice and see our data in many different ways. What is needed is a way to filter, organize and report on data that hasn’t been decomposed into tables.See alsoGuide to ViewsView ModelTo address this problem of adding structure back to unstructured and semi-structured data, CouchDB integrates a view model. Views are the method of aggregating and reporting on the documents in a database, and are built on-demand to aggregate, join and report on database documents. Because views are built dynamically and don’t affect the underlying document, you can have as many different view representations of the same data as you like.View definitions are strictly virtual and only display the documents from the current database instance, making them separate from the data they display and compatible with replication. CouchDB views are defined inside special design documents and can replicate across database instances like regular documents, so that not only data replicates in CouchDB, but entire application designs replicate too.Javascript View FunctionsViews are defined using Javascript functions acting as the map part in a map-reduce system. A view function takes a CouchDB document as an argument and then does whatever computation it needs to do to determine the data that is to be made available through the view, if any. It can add multiple rows to the view based on a single document, or it can add no rows at all.See alsoView functionsView IndexesViews are a dynamic representation of the actual document contents of a database, and CouchDB makes it easy to create useful views of data. But generating a view of a database with hundreds of thousands or millions of documents is time and resource consuming, it’s not something the system should do from scratch each time.To keep view querying fast, the view engine maintains indexes of its views, and incrementally updates them to reflect changes in the database. CouchDB’s core design is largely optimized around the need for efficient, incremental creation of views and their indexes.
Views and their functions are defined inside special “design” documents, and a design document may contain any number of uniquely named view functions. When a user opens a view and its index is automatically updated, all the views in the same design document are indexed as a single group.
The view builder uses the database sequence ID to determine if the view group is fully up-to-date with the database. If not, the view engine examines the all database documents (in packed sequential order) changed since the last refresh. Documents are read in the order they occur in the disk file, reducing the frequency and cost of disk head seeks.
The views can be read and queried simultaneously while also being refreshed. If a client is slowly streaming out the contents of a large view, the same view can be concurrently opened and refreshed for another client without blocking the first client. This is true for any number of simultaneous client readers, who can read and query the view while the index is concurrently being refreshed for other clients without causing problems for the readers.
As documents are processed by the view engine through your ‘map’ and ‘reduce’ functions, their previous row values are removed from the view indexes, if they exist. If the document is selected by a view function, the function results are inserted into the view as a new row.
When view index changes are written to disk, the updates are always appended at the end of the file, serving to both reduce disk head seek times during disk commits and to ensure crashes and power failures can not cause corruption of indexes. If a crash occurs while updating a view index, the incomplete index updates are simply lost and rebuilt incrementally from its previously committed state
1.1.5. Security and Validation
To protect who can read and update documents, CouchDB has a simple reader access and update validation model that can be extended to implement custom security models.
See also
/db/_security
Administrator Access
CouchDB database instances have administrator accounts. Administrator accounts can create other administrator accounts and update design documents. Design documents are special documents containing view definitions and other special formulas, as well as regular fields and blobs.
Update Validation
As documents written to disk, they can be validated dynamically by javascript functions for both security and data validation. When the document passes all the formula validation criteria, the update is allowed to continue. If the validation fails, the update is aborted and the user client gets an error response.
Both the user’s credentials and the updated document are given as inputs to the validation formula, and can be used to implement custom security models by validating a user’s permissions to update a document.
A basic “author only” update document model is trivial to implement, where document updates are validated to check if the user is listed in an “author” field in the existing document. More dynamic

ผลลัพธ์ (ไทย) 3:

1.1 . สำหรับภาพรวมทางเทคนิค
. จัดเก็บเอกสารการ couchdb เซิร์ฟเวอร์โฮสต์ชื่อฐานข้อมูล จัดเก็บเอกสาร เอกสารแต่ละอย่างชื่อในฐานข้อมูล และ couchdb ให้ arestful HTTP API สำหรับการอ่านและปรับปรุง ( เพิ่ม , แก้ไข , ลบ ) เอกสารฐานข้อมูล .
เอกสารเป็นหน่วยหลักของข้อมูลใน couchdb และประกอบด้วยจำนวนของเขตข้อมูลและสิ่งที่แนบมาเอกสารยังรวมถึงข้อมูลที่ดูแลระบบฐานข้อมูล ด้านเอกสาร มี ชื่อ และประกอบด้วยค่าของชนิดที่แตกต่างกัน ( ข้อความ , ตัวเลข , ตรรกะ , รายชื่อ , ฯลฯ ) และไม่มีการกำหนดวงเงินให้ขนาดตัวอักษรหรือนับองค์ประกอบ
ปรับปรุงเอกสาร couchdb แบบ lockless และมองโลกในแง่ดี เอกสารการแก้ไขที่ทำโดยโปรแกรมไคลเอนต์โหลดเอกสาร การสมัคร การเปลี่ยนแปลงและบันทึกกลับไปที่ฐานข้อมูล ถ้าลูกค้าคนอื่นแก้ไขเอกสารเดียวกันจะทำการบันทึกการเปลี่ยนแปลงของพวกเขาแรกลูกค้าจะได้รับการแก้ไขความขัดแย้ง เกิดข้อผิดพลาดในการบันทึก แก้ไข ปรับปรุง การจัดการความขัดแย้ง รุ่นของเอกสารล่าสุดสามารถเปิด แก้ไข และปรับปรุงนํามาใช้อีกพยายามอีกครั้ง .
ปรับปรุงเอกสาร ( เพิ่ม , แก้ไข , ลบ ) ทั้งหมดหรือไม่มีอะไรทำทั้งหมด หรือ ล้มเหลว โดยสิ้นเชิงฐานข้อมูลไม่เคยมีบางส่วนบันทึกหรือแก้ไขเอกสาร
1.1.2 . คุณสมบัติของกรด
couchdb ไฟล์รูปแบบและระบบความมุ่งมั่นทั้งหมดสอดคล้องแยกอะตอมคุณสมบัติทนทาน ( กรด ) คุณสมบัติ บนดิสก์ couchdb ไม่เคยเขียนทับได้ข้อมูลหรือโครงสร้างที่เกี่ยวข้องมั่นใจได้ว่าไฟล์ฐานข้อมูลอยู่ในสถานะที่สอดคล้องกันนี้คือ " ชน " เท่านั้น การออกแบบที่ couchdb เซิร์ฟเวอร์ไม่ได้ไปปิดกระบวนการมันก็สิ้นสุดลง
ปรับปรุงเอกสาร ( เพิ่ม , แก้ไข , ลบ ) จะเป็นอันดับ ยกเว้นการไบนารีที่เขียนไว้พร้อม ฐานข้อมูลผู้อ่านไม่เคยล็อคออก และไม่ต้องรอเมื่อผู้เขียนหรือผู้อ่านอื่น ๆหมายเลขใด ๆของลูกค้าสามารถอ่านเอกสารโดยไม่ถูกล็อคออกหรือถูกรบกวนโดยการปรับปรุงพร้อมกัน แม้ในเอกสารเดียวกัน couchdb อ่านการใช้มัลติรุ่นการควบคุม ( mvcc ) รุ่นที่ลูกค้าแต่ละรายจะเห็นภาพรวมที่สอดคล้องกันของฐานข้อมูลจากจุดเริ่มต้นไปยังจุดสิ้นสุดของ
อ่านการดําเนินงานเอกสารดัชนีใน b-trees โดยชื่อของพวกเขา ( docid ) และลำดับ ID แต่ละการปรับปรุงฐานข้อมูลตัวอย่างสร้างหมายเลขลำดับใหม่ ลำดับ รหัสที่ใช้ในภายหลังสำหรับการเปลี่ยนแปลงแบบเพิ่มหน่วยค้นหาในฐานข้อมูล ดัชนีต้นไม้เหล่านี้มีการปรับปรุงพร้อมกัน เมื่อมีเอกสารบันทึกหรือลบ ดัชนีการปรับปรุงมักจะเกิดขึ้นที่ส่วนท้ายของแฟ้ม ( .
อัพเดทเท่านั้น )