| commit | d26141d6b1c09783350e5e1906d5e71bc10071f0 | [log] [tgz] |
|---|---|---|
| author | luochen01 <cluo8@uci.edu> | Fri Jun 02 22:28:15 2017 -0700 |
| committer | Yingyi Bu <buyingyi@gmail.com> | Sat Jun 03 08:45:35 2017 -0700 |
| tree | 50188affa1013dac28993bd5bc3a6a5b9bede822 | |
| parent | 46518babd57147b66c4016cea520687ccfaf60c1 [diff] |
Allow insert anti-matter tuples when bulk loading LSM index Previously, when we bulk load an LSM index, we are not allowed to insert anti-matter tuples to the disk component. However, creating secondary index for correlated datasets requires anti-matter tuples to be inserted as well. Thus, this patch mainly contains the following changes: - When bulk loading LSM index, allow the user to switch between insert mode and delete mode - Extended the LSMDiskComponentBulkLoader with the delete method. For LSM index with anti-matter tuples, the delete method simply sets the TupleWriter to delete mode, and inserts the anti-matter tuple. For LSM index with buddy btree, it simply inserts the deleted tuple into the buddy btree. - Since the LSMDiskComponentBulkLoader would have a delete method anyway, added a new ILSMDiskComponentBulkLoader interface containing the delete method. Change-Id: I6665f56a5d2183697197298fa24824eeb827686a Reviewed-on: https://asterix-gerrit.ics.uci.edu/1796 Sonar-Qube: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu> BAD: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Reviewed-by: Yingyi Bu <buyingyi@gmail.com> Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
AsterixDB is a BDMS (Big Data Management System) with a rich feature set that sets it apart from other Big Data platforms. Its feature set makes it well-suited to modern needs such as web data warehousing and social data storage and analysis. AsterixDB has:
Data model
A semistructured NoSQL style data model (ADM) resulting from extending JSON with object database ideas
Query languages
Two expressive and declarative query languages (SQL++ and AQL) that support a broad range of queries and analysis over semistructured data
Scalability
A parallel runtime query execution engine, Apache Hyracks, that has been scale-tested on up to 1000+ cores and 500+ disks
Native storage
Partitioned LSM-based data storage and indexing to support efficient ingestion and management of semistructured data
External storage
Support for query access to externally stored data (e.g., data in HDFS) as well as to data stored natively by AsterixDB
Data types
A rich set of primitive data types, including spatial and temporal data in addition to integer, floating point, and textual data
Indexing
Secondary indexing options that include B+ trees, R trees, and inverted keyword (exact and fuzzy) index types
Transactions
Basic transactional (concurrency and recovery) capabilities akin to those of a NoSQL store
Learn more about AsterixDB at its website.
To build AsterixDB from source, you should have a platform with the following:
Instructions for building the master:
Checkout AsterixDB master:
$git clone https://github.com/apache/asterixdb.git
Build AsterixDB master:
$cd asterixdb $mvn clean package -DskipTests
Here are steps to get AsterixDB running on your local machine:
Start a single-machine AsterixDB instance:
$cd asterixdb/asterix-server/target/asterix-server-*-binary-assembly/ $./opt/local/bin/start-sample-cluster.sh
Good to go and run queries in your browser at:
http://localhost:19001
Read more documentations to learn the data model, query language, and how to create a cluster instance.