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BARREL BUILD A P2P DOCUMENT
 ORIENTED DATABASE https://barrel-db.org Erlang Factory San Francisco 2016

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VISION AND CONCEPT

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local database mobile sensor "cloud" database local database mobile DATA IS MOBILE

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share discover replicate PEER TO PEER (P2P)

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▸ Local first ▸ Put/Match the data next to you ▸ Query Locally ▸ Replicate a view of the data you need

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WHAT IS BARREL

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WHAT IS BARREL ▸ a document database ▸ document are JSON with attachments and links ▸ changes feed for document and indexes ▸ replication between any nodes in both way ▸ views (~ map) ▸ HTTP 1.1/2 API

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▸ DATA: not just blobs ▸ Replicated APPs ▸ Couchapps but extended and revisited REPLICATED APPS

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DECONSTRUCT

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APPEND ONLY & MVCC Doc1 Doc2 Doc3 Doc4 Doc5 Doc6 Doc7 Btree Node Btree Node Document revision Block btree node invalid data version

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▸ Create a new file to remove the fragmentation ▸ A race between copy and the addition of new data ▸ Require at least twice of the storage THE COMPACTION ISSUE

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DOCUMENT STORAGE ID 1 METADATA 1 ID 2 METADATA 2 ID 3 METADATA 3 ID-Index SEQ 1 METADATA 1 SEQ 2 METADATA 2 SEQ 3 METADATA 3 Seq-Index Btree Node Btree Node Doc Indexed document DB file

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▸ 2 indexes (btree): by sequence, by id ▸ 1 index for local documents without conflict handling ▸ A revision tree is stored in indexes pointed to the revision offset ▸ The revision is stored in the file separately HOW ARE STORED DOCUMENTS

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▸ Reverse index (map) ▸ Index using a function ▸ Function in javascripts, erlang, .. ▸ Incremental index ▸ Retrieves changes (aka view changes) ▸ View are regrouped by groups (1 db file/group) VIEWS

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VIEW STORAGE DOCID View 1 KEY 1 SEQ 1 ADD KEY 2 SEQ 2 DEL View 2 KEY 1 SEQ 1 ADD Log-Index [KEY 1, DOCID] [VALUE, DOCREV, SEQ] [KEY 2, DOCID] [del, DOCREV, SEQ] [KEY 3, DOCID 2] [VALUE, DOCREV, SEQ] Key-Index [SEQ 1, KEY] [VALUE, DOCREV, SEQ] [SEQ 2, KEY 2] [del, DOCREV, SEQ] [SEQ 3, KEY]3 [VALUE, DOCREV, SEQ] SEQ-Index view

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REVISION TREE

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BUILT IN ERLANG /> <

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▸ Write is slow ▸ Read should not being blocked by writes ▸ No shared memory ▸ No atomic integer trick ▸ Only actors and message passing ▸ Operations on a doc are atomic CHALLENGES

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READ/WRITE OPERATIONS DB STATE READER READER writer writer update share state

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▸ LRU to cache blocks
 https://github.com/barrel-db/erlang-lru ▸ 1 File process, Operations are limited ▸ DB users are linked to the database process ▸ Optional Write buffer to reduce the latency ▸ Optional wal READ/WRITE OPERATIONS

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▸ STORE SEGMENTS of data for compaction ▸ IO is "relatively" slow in erlang ▸ USE a “native KV store” as a nif. SPEEDUPS

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INDEX OPERATIONS View Group READER READER change reader indexer update share state send /collect changes DB get changes

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▸ Credit Flow Based ▸ The View group keep the state ▸ View group is created on demande ▸ kept open until it has readers ▸ Indexer ask for updates ▸ Read functions (Map functions) are processed in // INDEX OPERATIONS

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▸ Added 2 features: ▸ MOVE: move doc(s) to another node or database (like copy but with delet ▸ User hooks functions (run in background) using hooks:
 https://github.com/barrel-db/hooks ▸ Partition on demand ▸ Decision depends on the application needs NEW FUNCTIONS

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CHANGES HANDLER subscriber change dispatcher broadcast changes DB

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▸ Use the sequence index ▸ changes load balancing ▸ consumer subscribe on patterns (delete, update, …) ▸ Create changes Load Balancer on demand ▸ Allows remote nodes to subscribe to a queue ▸ Based on primer (release on March 2016) CHANGES EVENTS

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▸ Use the sequence index ▸ changes load balancing ▸ consumer subscribe on patterns (delete, update, …) ▸ Create changes Load Balancer on demand ▸ Allows remote nodes to subscribe to a queue ▸ Based on primer (release on March 2016) CHANGES EVENTS

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▸ inherited the HTTP api in mochiweb ▸ small changes to makes the server more resilient ▸ chatterbox ▸ wip in cowboy. ▸ yaws ? HTTP API

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P2P

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▸ Over HTTP ▸ Replication is the core ▸ Each nodes can replicate each others ▸ PUSH/PULL ▸ Chained replication P2P

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▸ Based ont the change feed ▸ fetch the revisions and their attachments
 not present on the node ▸ continuous or not ▸ try to collect multiple docs at once ▸ use hackney:
 http://github.com/benoitc/hackney ▸ Use a Flow-based pattern instead of a classic pool REPLICATION

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REPLICATION OPERATIONS replication worker replication proxy fetch docs DB SOURCE get changes DB TARGET notify changes push docs

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▸ Replication state is stored a least on one node ▸ checkpoints ▸ get the revisions not actually stored on the nodes (“_rev_diffs” ▸ the replication proxy maintains routes ▸ build replication chains, by replicating status REPLICATION

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HTTPS://BARREL-DB.ORG Barrel HTTP://ENKIM.EU Enki Multimedia