jm + persistence   8

Intel pcj library for persistent memory-oriented data structures
This is a "pilot" project to develop a library for Java objects stored in persistent memory. Persistent collections are being emphasized because many applications for persistent memory seem to map well to the use of collections. One of this project's goals is to make programming with persistent objects feel natural to a Java developer, for example, by using familiar Java constructs when incorporating persistence elements such as data consistency and object lifetime.

The breadth of persistent types is currently limited and the code is not performance-optimized. We are making the code available because we believe it can be useful in experiments to retrofit existing Java code to use persistent memory and to explore persistent Java programming in general.


(via Mario Fusco)
persistent-memory  data-structures  storage  persistence  java  coding  future 
10 weeks ago by jm
Intel speeds up etcd throughput using ADR Xeon-only hardware feature
To reduce the latency impact of storing to disk, Weaver’s team looked to buffering as a means to absorb the writes and sync them to disk periodically, rather than for each entry. Tradeoffs? They knew memory buffers would help, but there would be potential difficulties with smaller clusters if they violated the stable storage requirement.

Instead, they turned to Intel’s silicon architects about features available in the Xeon line. After describing the core problem, they found out this had been solved in other areas with ADR. After some work to prove out a Linux OS supported use for this, they were confident they had a best-of-both-worlds angle. And it worked. As Weaver detailed in his CoreOS Fest discussion, the response time proved stable. ADR can grab a section of memory, persist it to disk and power it back. It can return entries back to disk and restore back to the buffer. ADR provides the ability to make small (<100MB) segments of memory “stable” enough for Raft log entries. It means it does not need battery-backed memory. It can be orchestrated using Linux or Windows OS libraries. ADR allows the capability to define target memory and determine where to recover. It can also be exposed directly into libs for runtimes like Golang. And it uses silicon features that are accessible on current Intel servers.
kubernetes  coreos  adr  performance  intel  raft  etcd  hardware  linux  persistence  disk  storage  xeon 
may 2015 by jm
Simple Binary Encoding
'SBE is an OSI layer 6 representation for encoding and decoding application messages in binary format for low-latency applications.'

Licensed under ASL2, C++ and Java supported.
sbe  encoding  codecs  persistence  binary  low-latency  open-source  java  c++  serialization 
december 2013 by jm
Lightning Memory-Mapped Database
Sounds like a good potential replacement for Berkeley DB, at least for cases where LevelDB isn't proving practical.
LMDB is a database storage engine similar to LevelDB or BDB which database authors often use as a base for building databases on top of. LMDB was designed as a replacement for BDB within the OpenLDAP project but it has been pretty useful to use with other databases as well. It’s API design is highly influenced by BDB so that replacing BDB is straightforward.


Licensed under the OpenLDAP Public License (is that BSDish?)
openldap  lmdb  databases  bdb  berkeley-db  storage  persistence  oss  open-source 
july 2013 by jm
HyperLevelDB: A High-Performance LevelDB Fork
'HyperLevelDB improves on LevelDB in two key ways:
Improved parallelism: HyperLevelDB uses more fine-grained locking internally to provide higher throughput for multiple writer threads.
Improved compaction: HyperLevelDB uses a different method of compaction that achieves higher throughput for write-heavy workloads, even as the database grows.'
leveldb  storage  key-value-stores  persistence  unix  libraries  open-source 
june 2013 by jm
SSTable and Log Structured Storage: LevelDB
good writeup of LevelDB's native storage formats; the Sorted String Table (SSTable), Log Structured Merge Trees, and Snappy compression
leveldb  nosql  data  storage  disk  persistence  google 
july 2012 by jm

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