Hi Ming Wen I am quit sorry, i make a reformat.
Here is my project info. ==================== Dear Apache Incubator Community, Please accept the following proposal for presentation and discussion: https://github.com/lucene-cn/lxdb/wiki LXDB is a high-performance,OLAP,full text search database.it`s base on hbase,but replaced hfile with lucene index to support more effective secondary indexes,it`s also base on spark sql,so that you can used sql api to visit data and do olap calculate. and also the lucene index is store on hdfs (not local disk). In our Production System, LXDB supported 200+ clusters,some of the single cluster is 1000+ nodes,insert 200 billion rows per day ( 20000 billion rows for total), one of the biggest single table has 200million lucene index on LXDB. Hadoop`s father Doug Cutting cut nutch into HBase, MapReduce (hive), HDFS, Lucene.We have merged these separated projects again,LXDB equals spark sql+hbase+lucene+parquet+hdfs,it is a super database.It took me 10 years to complete these merging operations.But the purpose is no longer a search engine, but a database. Best regards yannian mu LXDB Proposal == Abstract == LXDB is a high-performance,OLAP,full text search database. === it`s base on hbase,but replaced hfile with lucene index to support more effective secondary indexes.=== we modify hbase region server ,we change hfile to lucene,when put data we put document to lucene instande of put data to hfile lucene index store on region server (it is not sote in different cluster like elstice search+hbase ,it takes to copy of data) === it`s base on spark sql for olap=== we Integrated spark and hbase together ,it`s useage like this , 1.unpackage lxdb.tar.gz 2.config hadoop_config path, 3.run start-all.sh to start cluster. lxdb can startup spark through hadoop yarn ,and then spark executor process Embedded start hbase region server service . you can operate lxdb database throuth spark sql api(hive) or mysql api. 1.the sql used spark rdd+hbase scaner to visit hbase . 2.the sql`s condition (filter or group by agg) will predicate to hbase , 3.hbase used lucene index to filter data in region server. all of the spark,hbase,lucene is Embedded Integrated together,it is not a seperate cluster ,that is the different with solr/es + hbase+spark Solution. == Background == === Multiple copies of data === Apache HBase+Elastic Search is the most popular Solution on full text search ,but it`s weak on Online AnalyticalProcessing. so most of the time the Production System used spark(or hive or impala or presto) ,hbase,solr/es at the same time.Multiple copies of data are stored in multiple systems,multiple systems has different Api .Data consistency is difficult to guarantee.For the above reasons we merger spark,hbase,elastic into one project .it`s target is used one copy of data,one cluster,one api to solve olap,kv,full text...database scenarios. === Merging and splitting of lucene indexes(hstore) acrocess different machine on hdfs === As we all know solr/es store file in local fileSystem,it`s shard num must be a fix num,but if we store index on hdfs,the index can split able like hbase hstore,it can split or merge acorss machine nodes ,this is very usefull for distribute database ,it depend malloc how much resource on a table,most of time the records of a table is different by time by time so the num of shards always need adjust,if index store local it can`t split acroces throw different machine ,but lucene index store on hdfs it`s can do it. whether the number of pieces can be flexibly adjusted, whether it has the ability of elastic scaling, in a distributed database is particularly important === solved Insufficient of secondary indexes === some people use hbase secondary index like Phoenix prjoect. but those programme base on the hbase rowkey has a lot of redundancy,He can't create too many indexes,Data inflation rate is too high,so used lucene index instand of secondary is the best chooses. === we add an lucene index for spark olap=== Most of OLAP systems has violent scanning problems and Poor timeliness of data like hive,spark sql,impala or some of the mpp database. 1.They used violent scans to calculate the data.but another choice is add index to the big data.some of the time using index can greatly improve the performance of the original brute force scanning. i think that just like the traditional database, indexing technology can greatly improve the performance of the speed database. 2.Another problem of thoses database or system, Most of them are an offline system or batch system,lxdb `s target is realtime append ,realtime kv update just like hbase. ==future== === lucene on parquet === recenetly i will change lucene tim,tip(invert index) ,dvd,dvm files to like parquet or orc format. To solve the performance problem of traversing Lucene index.To solve the problem that opening Lucene file needs to load files such as tip into memory, which leads to slow opening Lucene index file,To enable Lucene to store multi column joint index by column, which is used to handle some logic such as multi table join and materialized view ,mulity fields group by by invert index,The current Lucene index has many problems because of too many file pointers and single column problems,We want to modify Lucene to make it more suitable for HDFS, not only for full-text retrieval, but also better at statistical analysis, which is a real database level index,We want Lucene to be splitable, which can separate storage from computation. === supporting all kinds of Predicate pushdown calculation === We find that if we can combine the calculation method with the data closely, we can give more play to the performance of the database. Index is only a way of calculating push down. For example, storage push down, we can store the index on the SSD device, and the data part on the SATA device. We can store the data that are often grouped together in advance, instead of calculating line by line, We can give important tables or columns to dedicated devices and resources, but these hbases are still lacking, which we need to further improve === Distribution of intervention data === we can used row key to intervention data to different nodes ,it can do many interestest things === Resource control, resource isolation === lucene recent is not support resource isolation,but on hdfs we can do it , I can control the priority of SQL so that Lucene with higher priority can get faster IO resources. == Status == since 2011 I released the first open source version on Alibaba ,At that time, mdrill used 10 nodes 48g machines to support 400 billion data. the first index on hdfs is from this version.it`s one year ahead of the community. https://github.com/alibaba/mdrill . since 2014 i stoped mdrill project update for the reason of i join into tencent . in our team we developed hermes project ,we also build lucene on hdfs , hermes now realtime import 1000 billion rows of data per day.It's the largest database I've ever developed , https://plus.tencent.com/bigdata/hermes since 2018 I set up my own company called luxin, Lu Xin is the Chinese pronunciation of Lucene. as a funs of lucene ,luxin company`s domain is lucene.xin ,mail domain is lucene.cn. luxin`s first version of lxdb is called lsql,it`s means lucene sql. it used lucene(2.5.3)+hdfs+spark(1.6.3),it is stable, about 200+ of cluster use lsql. it`s process about 200 billions per day ,amount of 20000 billions rows in one single cluster. (1000 nodes) since 2010 In the case of COVID-19 our team decide to developed the next generation of lsql called lxdb(lx=lucene pronunciation ). we add hbase to lsql To solve the update problem.nowadays we have finish the first version of lxdb. https://github.com/lucene-cn/lxdb/wiki == Known Risks == ==Meritocracy == lxdb has been deployed in production and is applying more than 200 lines of business. It has demonstrated great performance benefits and has proved to be a better way for reporting and analysis based big data. Still We look forward to growing a rich user and developer community. === Orphaned products === The core developers currently work full-time for Luxin. lxdb is widely adopted by many companies and individuals. There's no realistic chance of it becoming orphaned. and we have a number of 1000 person tencent qq Instant messaging group === Inexperience with Open Source=== The core developers are all active users and followers of open source. They are already committers and contributors to the lxdb project. developed yannian mu has tens years on open source project, jstorm https://github.com/alibaba/jstorm and mdrill https://github.com/alibaba/mdrill === Homogenous Developers === The most of core developers are from luxin for the Closed source products reason, but when lxdb was open sourced, lxdb will received a lot of bug fixes and enhancements from other developers not working at luxin.Where did you learn it from and where did you return it. ===Reliance on Salaried Developers === Lxin invested in lxdb as the solution and some of its key engineers are working full time on the project. In addition, since there is a growing Big Data need for scalable solutions, we look forward to other Apache developers and researchers to contribute to the project. Also key to addressing the risk associated with relying on Salaried developers from a single entity is to increase the diversity of the contributors and actively lobby , Apache lxdb intends to do this. === An Excessive Fascination with the Apache Brand === Lxdb is proposing to enter incubation at Apache in order to help efforts to diversify the committer-base, not so much to capitalize on the Apache brand. The Lxdb project is in production use already inside lxdb, but is not expected to be an lxdb product for external customers. As such, the lxdb project is not seeking to use the Apache brand as a marketing tool. === Documentation=== Information about Palo can be found at https://github.com/lucene-cn/lxdb. The following links provide more information about lxdb in open source: * wiki site: https://github.com/lucene-cn/lxdb/wiki * Issue Tracking: https://github.com/lucene-cn/lxdb/issues * Overview: https://github.com/lucene-cn/lxdb/wiki/intro * lxin home page: http://www.lucene.xin * lsql document: http://docs.lucene.xin/lsql/v21/ ##Initial Source lxdb will development source code under an Apache license at https://github.com/lucene-cn/lxdb. === Core Developers === Currently most of the core developers of LXDB are working in the research Team of luxin. - yannian mu (dev) - yu chen (dev) - guangshi hao (dev) - wei sun (dev) - qihua zheng (dev) - xin wang (dev) - qingsong liu (dev) - anxing zhou (Tester) - jiajun duan (Tester) == External Dependencies == As all dependencies are managed using Apache Maven Dependency License Optional? lucene Apache License 2.0 true zookeeper Apache License 2.0 true hbase Apache License 2.0 true spark Apache License 2.0 true hadoop Apache License 2.0 true hive Apache License 2.0 true == Required Resources == === Mailing lists === * lxdb-private (PMC discussion) * lxdb-dev (developer discussion) * lxdb-user (user discussion) * lxdb-commits (SCM commits) * lxdb-issues (JIRA issue feed) === Subversion Directory === Instead of subversion, LXDB prefers to git as source control management system: git://git.apache.org/lxdb ===Different from carbondata and clickhouse=== When carbondata appeared in 2015, it was a product that shocked me very much. Adding a layer of index to big data is what I have been doing all these years. I didn't expect that there would be a team in this world with the same idea as me,They are all based on Hadoop, and even the startup is based on spark on yarn Everyone is based on spark, and its core is the underlying data structure of spark. We can improve the speed of spark by unique data format such as index,Whether the data has an index and whether the index is stored on the local disk or HDFS is a significant feature that distinguishes us from other analytical databases, such as hive, spark SQL, impala and some MAPP databases,On this point, we are consistent with carbontata Our team later spent a certain amount of energy to do a test with carbontata, and the positioning in some directions is still very different,As for Clickhouse, I didn't come across many projects before. Until one day, when I was recruiting in the group, someone asked me, is your product as fast as Clickhouse? Therefore, I knew that there was such a good product in the industry, #1 Coarse grained index vs fine-grained index, or index stored by block and index not stored by block, We found that the writing speed of carbondata and Clickhouse is very fast, while we used lxdb and elastic search at the same time, because both of them are based on Lucene, which is an order of magnitude lower than the former two #2 Later, we found that the main difference lies in the way of index. One is the index by block, and the other is the overall global index. The former is very fast in storage, and it is easier to separate index and calculation. Even carbondata is a real cloud native database (the Clickhouse data is stored locally, not cloud native), But the benefit is not only the improvement of single column filtering, but also the improvement of multi condition combination filtering and the convenience of updating. If the former is not handled properly, it is easy to cause full scan, but there will be a high cost to realize updating, The latter can be combined with BitSet or bloom filter to realize the combination of multi column conditions, and the global index is more suitable for updating. Therefore, lxdb and es have the characteristics of real-time updating. This is why we are different from carbondata. We inherit a HBase in comparison, and the main purpose is to realize the real-time updating of kV level, In the future, if lxdb wants to take a step on the cloud native Road, it is bound to make some innovations and changes in the index format of Lucene #3 Because lxdb is bound to HBase in the future, OLTP at kV level is also a direction in the future #4 In terms of statistical analysis, the performance of docvalues used by Lucene is not as good as that of carbondata and clickhouse,Because of this reason, I spent some experience to improve the performance of random reading on HDFS, and the speed can be increased by 100-200 times. But I think the code to modify HDFS will lead to poor compatibility of our products in the customer platform in the future, and will force customers to replace Hadoop with our version. I didn't choose this scheme in the end, This is the address of my improvement project https://github.com/lucene-cn/lxhadoop One of the ideas that came to my mind later is to replace the format of parquet with the inverted and forward row of Lucene, so that I can carry out multi condition full-text retrieval. The multi column feature of parquet allows me to avoid the performance problem of random reading by efficiently traversing the inverted table ####Different from alibaba analytic db#### I'm not particularly familiar with analyticdb, so I just looked up some information through the search engine. If there is any misunderstanding, please criticize and correct me Most of the time they are really similar,Analyticdb is a very excellent database, but its technical principles can hardly be found on the Internet. From my personal point of view, they may have the following differences #1)Analyticdb is a cloud native data warehouse in the full sense,This is also the feature they added to the new edition, which supports the separation of storage and computing, and the time-sharing flexibility of resources on demand. The same piece of data can start different computing resources at different computing nodes according to different computing However, lxdb is not a real cloud native database. Although we store the Lucene index on HDFS, we can only separate the storage from computing. At present, when the Lucene itself is opened for the first time, the index information such as tip must be preloaded into memory, which leads to the persistent opening of Lucene in the resident process, Therefore, lxdb has not been able to separate computing from computing, that is, it has not been able to distribute computing resources to different processes according to different queries. This has always been a pity of lxdb, so I have been trying these years At present, cloud native database has great market potential, and we are willing to try it,And I know that it's not difficult to change Lucene like this, or it's less difficult than integrating spark, HBase and Lucene together. #2)Analyticdb can't be built by itself, it can only run on the cloud platform provided by it,Must be purchased with the underlying cloud environment, which sometimes gives users more restrictions. Lxdb is based on Hadoop platform. As long as users have Hadoop environment, lxdb can directly start services through yard, which is suitable for private deployment and deployment on the cloud, and it doesn't limit any manufacturers. It is relatively open #3)I feel that it is more like a batch engine,It is more like a scene of centralized import and batch query,At least his cloud native model should be like this,Or I didn't find the user manual for real-time import , while lxdb is a real-time engine with low data latency,Relatively speaking, it is easier for batch engine to realize cloud native, while it is more difficult for real-time millisecond delay engine to realize the separation of storage and computing. It needs a snapshot mechanism to record the data change at a certain time, so as to realize the separation of computing and computing between different nodes #4 According to the official documents, see specifications and restrictions, the best configuration is C32. The number of nodes supported by C32 is less than 128, and the storage capacity is 1PB. In the production environment, lxdb has 904 nodes, 50pb disk capacity, and 70% storage utilization,Of course, it can be inaccurate and unfair to adb. f...@lucene.cn yannian mu f...@lucene.cn yannian mu From: Ming Wen Date: 2021-02-28 21:18 To: general Subject: Re: Re: [Proposal] lxdb - proposal for Apache Incubation Hi, fp, Your email is hard to read. Please change to a normal mail client first. Back to your proposal, the key concern is not technology, but IPMC can not evaluate a project when we can see anything. Thanks, Ming Wen, Apache APISIX PMC Chair Twitter: _WenMing f...@lucene.cn <f...@lucene.cn> 于2021年2月28日周日 下午9:02写道： > Hi Furkan Kamaci > > > Thank you for your proposal, I will start to improve and prepare > > > > > 1.Find an experienced mentor to guide you. > > > > todo > > > > 2.Start to translate your documentation to English. > > > > 3.Open source your project. How can we have a comment on your project if > > > > we cannot see anything about it? > > > > > > > > give me some time,I discussed with my team, my English is too poor. > > > > > > > > 4) Gain contributors to your project. At least you should show your > > > > intention to have committers/contributors out of your company. Eliminate > > > > the risk of being non-meritocratic management of the project. > > > > > > > > That's what I have to do > > > > > > > > 5) Structure your proposal. Explain why people need this project, which > > > > problems do current projects have and how you managed to handle them. We > > > > should understand is it a bundle of other projects, a completely new > > > > project, or a wrapper of other projects which eliminates the shortcomings > > > > of them. > > > > 6) Find a suitable name for your project in order to not try to solve > > > > trademark problems that may lose your time if you enter the incubation. > > > > > > > > ok i thike a new name ,for example like hydrogen sql > > > > > > > > > > > > > > > > f...@lucene.cn yannian mu > > > > > > > > From: Furkan KAMACI > > > > Date: 2021-02-28 18:51 > > > > To: general > > > > Subject: Re: [Proposal] lxdb - proposal for Apache Incubation > > > > Hi, > > > > > > > > Actually you have a detailed documentation which explains which approach > > > > you have compared to similar systems and performance metrics of following > > > > them i.e. reducing storage 10 to the 100 times or having low latency > > > > queries. > > > > > > > > My advices are (some of them are same with Sheng's and Liang's ): > > > > > > > > 1) Find an experienced mentor to guide you. > > > > > > > > 2) Start to translate your documentation to English. > > > > > > > > 3) Open source your project. How can we have a comment on your project if > > > > we cannot see anything about it? > > > > > > > > 4) Gain contributors to your project. At least you should show your > > > > intention to have committers/contributors out of your company. Eliminate > > > > the risk of being non-meritocratic management of the project. > > > > > > > > 5) Structure your proposal. Explain why people need this project, which > > > > problems do current projects have and how you managed to handle them. We > > > > should understand is it a bundle of other projects, a completely new > > > > project, or a wrapper of other projects which eliminates the shortcomings > > > > of them. > > > > > > > > 6) Find a suitable name for your project in order to not try to solve > > > > trademark problems that may lose your time if you enter the incubation. > > > > > > > > Kind Regards, > > > > Furkan KAMACI > > > > > > > > > > > > On Sun, Feb 28, 2021 at 1:02 PM Liang Chen <chenliang6...@gmail.com> > wrote: > > > > > > > > > Hi > > > > > > > > > > It would be better if you could find an experienced IPMC member to help > you > > > > > for preparing the proposal. > > > > > Based on Sheng Wu input, i have one more comment : can you please explain > > > > > what are the different with other similar data analysis DB? you can > > > > > consider explaining from use cases perspective. > > > > > > > > > > Regards > > > > > Liang > > > > > > > > > > > > > > > fp wrote > > > > > > Dear Apache Incubator Community, > > > > > > > > > > > > > > > > > > Please accept the following proposal for presentation and discussion: > > > > > > https://github.com/lucene-cn/lxdb/wiki > > > > > > > > > > > > > > > > > > LXDB is a high-performance,OLAP,full text search database.it`s base on > > > > > > hbase,but replaced hfile with lucene index to support more effective > > > > > > secondary indexes,it`s also base on spark sql,so that you can used sql > > > > > api > > > > > > to visit data and do olap calculate. and also the lucene index is store > > > > > on > > > > > > hdfs (not local disk). > > > > > > > > > > > > > > > > > > In our Production System, LXDB supported 200+ clusters,some of the > single > > > > > > cluster is 1000+ nodes,insert 200 billion rows per day ( 20000 > > > > > > billion rows for total), one of the biggest single table has 200million > > > > > > lucene index on LXDB. > > > > > > > > > > > > > > > > > > Hadoop`s father Doug Cutting cut nutch into HBase, MapReduce (hive), > > > > > HDFS, > > > > > > Lucene.We have merged these separated projects again,LXDB equals > > > > > > spark sql+hbase+lucene+parquet+hdfs,it is a super database.It took me > 10 > > > > > > years to complete these merging operations.But the purpose is no > longer a > > > > > > search engine, but a database. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > Best regards > > > > > > yannian mu > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > LXDB Proposal > > > > > > == Abstract == > > > > > > LXDB is a high-performance,OLAP,full text search database. > > > > > > > > > > > > > > > > > > === it`s base on hbase,but replaced hfile with lucene index to support > > > > > > more effective secondary indexes.=== > > > > > > we modify hbase region server ,we change hfile to lucene,when put > > > > > > data we put document to lucene instande of put data to > hfile > > > > > > lucene index store on region server (it is not sote in > > > > > > different cluster like elstice search+hbase ,it takes to copy of data) > > > > > > > > > > > > > > > > > > === it`s base on spark sql for olap=== > > > > > > we Integrated spark and hbase together ,it`s useage like this , > > > > > > 1.unpackage lxdb.tar.gz > > > > > > 2.config hadoop_config path, > > > > > > 3.run start-all.sh to start cluster. > > > > > > lxdb can startup spark through hadoop yarn ,and then spark executor > > > > > > process Embedded start hbase region server service . > > > > > > > > > > > > > > > > > > you can operate lxdb database throuth spark sql api(hive) or mysql api. > > > > > > 1.the sql used spark rdd+hbase scaner to visit hbase . > > > > > > 2.the sql`s condition (filter or group by agg) will predicate to hbase > , > > > > > > 3.hbase used lucene index to filter data in region server. > > > > > > all of the spark,hbase,lucene is Embedded Integrated together,it is > > > > > > not a seperate cluster ,that is the different with solr/es > + > > > > > > hbase+spark Solution. > > > > > > > > > > > > > > > > > > == Background == > > > > > > === Multiple copies of data === > > > > > > Apache HBase+Elastic Search is the most popular Solution on full text > > > > > > search ,but it`s weak on Online AnalyticalProcessing. > > > > > > so most of the time the Production System used spark(or hive or impala > or > > > > > > presto) ,hbase,solr/es at the same time.Multiple copies of data are > > > > > stored > > > > > > in multiple systems,multiple systems has different Api .Data > consistency > > > > > > is difficult to guarantee.For the above reasons we merger > > > > > > spark,hbase,elastic into one project .it`s target is used one copy of > > > > > > data,one cluster,one api to solve olap,kv,full text...database > scenarios. > > > > > > > > > > > > > > > > > > === Merging and splitting of lucene indexes(hstore) acrocess different > > > > > > machine on hdfs === > > > > > > As we all know solr/es store file in local fileSystem,it`s shard num > must > > > > > > be a fix num,but if we store index on hdfs,the index can split able > like > > > > > > hbase hstore,it can split or merge acorss machine nodes ,this is very > > > > > > usefull for distribute database ,it depend malloc how much resource on > a > > > > > > table,most of time the records of a table is different by time by time > so > > > > > > the num of shards always need adjust,if index store local it can`t > split > > > > > > acroces throw different machine ,but lucene index store on hdfs it`s > can > > > > > > do it. > > > > > > whether the number of pieces can be flexibly adjusted, whether it has > the > > > > > > ability of elastic scaling, in a distributed database is particularly > > > > > > important > > > > > > > > > > > > > > > > > > > > > > > > === solved Insufficient of secondary indexes === > > > > > > some people use hbase secondary index like Phoenix prjoect. but those > > > > > > programme base on the hbase rowkey has a lot of redundancy,He can't > > > > > create > > > > > > too many indexes,Data inflation rate is too high,so used lucene index > > > > > > instand of secondary is the best chooses. > > > > > > > > > > > > > > > > > > === we add an lucene index for spark olap=== > > > > > > Most of OLAP systems has violent scanning problems and Poor timeliness > of > > > > > > data like hive,spark sql,impala or some of the mpp database. > > > > > > 1.They used violent scans to calculate the data.but another choice is > add > > > > > > index to the big data.some of the time using index can greatly improve > > > > > the > > > > > > performance of the original brute force scanning. i think that > just > > > > > > like the traditional database, indexing technology can greatly improve > > > > > the > > > > > > performance of the speed database. > > > > > > 2.Another problem of thoses database or system, Most of them are an > > > > > > offline system or batch system,lxdb `s target is realtime append > > > > > ,realtime > > > > > > kv update just like hbase. > > > > > > > > > > > > > > > > > > ==future== > > > > > > === lucene on parquet === > > > > > > recenetly i will change lucene tim,tip(invert index) ,dvd,dvm > files > > > > > > to like parquet or orc format. > > > > > > To solve the performance problem of traversing Lucene index.To solve > the > > > > > > problem that opening Lucene file needs to load files such as tip into > > > > > > memory, which leads to slow opening Lucene index file,To enable Lucene > to > > > > > > store multi column joint index by column, which is used to handle some > > > > > > logic such as multi table join and materialized view ,mulity fields > group > > > > > > by by invert index,The current Lucene index has many problems because > of > > > > > > too many file pointers and single column problems,We want to modify > > > > > Lucene > > > > > > to make it more suitable for HDFS, not only for full-text retrieval, > but > > > > > > also better at statistical analysis, which is a real database level > > > > > > index,We want Lucene to be splitable, which can separate storage from > > > > > > computation. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > === supporting all kinds of Predicate pushdown > calculation === > > > > > > We find that if we can combine the calculation method with the data > > > > > > closely, we can give more play to the performance of the database. > Index > > > > > > is only a way of calculating push down. For example, storage push down, > > > > > we > > > > > > can store the index on the SSD device, and the data part on the SATA > > > > > > device. We can store the data that are often grouped together in > advance, > > > > > > instead of calculating line by line, We can give important tables or > > > > > > columns to dedicated devices and resources, but these hbases are still > > > > > > lacking, which we need to further improve > > > > > > > > > > > > > > > > > > === Distribution of intervention data === > > > > > > we can used row key to intervention data to different nodes ,it can do > > > > > > many interestest things > > > > > > > > > > > > > > > > > > === Resource control, resource isolation === > > > > > > lucene recent is not support resource isolation,but on hdfs > > > > > we > > > > > > can do it , I can control the priority of SQL so that Lucene with > higher > > > > > > priority can get faster IO resources. > > > > > > > > > > > > > > > > > > == Status == > > > > > > since 2011 I released the first open source version on Alibaba > ,At > > > > > > that time, mdrill used 10 nodes 48g machines to support 400 billion > data. > > > > > > the first index on hdfs is from this version.it`s one year ahead of > the > > > > > > community. https://github.com/alibaba/mdrill . > > > > > > > > > > > > > > > > > > since 2014 i stoped mdrill project update for the reason of i join into > > > > > > tencent . in our team we developed hermes project ,we also build > > > > > > lucene on hdfs , hermes now realtime import 1000 billion rows of data > per > > > > > > day.It's the largest database I've ever developed , > > > > > > https://plus.tencent.com/bigdata/hermes > > > > > > > > > > > > > > > > > > since 2018 I set up my own company called luxin, Lu Xin is the Chinese > > > > > > pronunciation of Lucene. as a funs of lucene ,luxin company`s domain is > > > > > > lucene.xin ,mail domain is lucene.cn. > > > > > > luxin`s first version of lxdb is called lsql,it`s means lucene > sql. > > > > > > it used lucene(2.5.3)+hdfs+spark(1.6.3),it is stable, about 200+ of > > > > > > cluster use lsql. it`s process about 200 billions per day ,amount of > > > > > 20000 > > > > > > billions rows in one single cluster. (1000 nodes) > > > > > > > > > > > > > > > > > > since 2010 In the case of COVID-19 our team decide to developed the > next > > > > > > generation of lsql called lxdb(lx=lucene pronunciation ). we add > > > > > > hbase to lsql To solve the update problem.nowadays we have finish the > > > > > > first version of lxdb. https://github.com/lucene-cn/lxdb/wiki > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > == Known Risks == > > > > > > ==Meritocracy == > > > > > > > > > > > > > > > > > > lxdb has been deployed in production and is applying more than 200 > lines > > > > > > of business. It has demonstrated great performance benefits and has > > > > > proved > > > > > > to be a better way for reporting and analysis based big data. Still We > > > > > > look forward to growing a rich user and developer community. > > > > > > > > > > > > > > > > > > === Orphaned products === > > > > > > > > > > > > > > > > > > The core developers currently work full-time for Luxin. > > > > > > lxdb is widely adopted by many companies and individuals. There's no > > > > > > realistic chance of it becoming orphaned. and we have a number of 1000 > > > > > > person tencent qq Instant messaging group > > > > > > > > > > > > > > > > > > > > > > > > === Inexperience with Open Source=== > > > > > > > > > > > > The core developers are all active users and followers of open source. > > > > > > They are already committers and contributors to the lxdb project. > > > > > > developed yannian mu has tens years on open source project, > jstorm > > > > > > https://github.com/alibaba/jstorm and > > > > > > mdrill https://github.com/alibaba/mdrill > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > === Homogenous Developers === > > > > > > > > > > > > > > > > > > The most of core developers are from luxin for the Closed source > products > > > > > > reason, but when lxdb was open sourced, lxdb will received a lot of bug > > > > > > fixes and enhancements from other developers not working at luxin.Where > > > > > > did you learn it from and where did you return it. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > ===Reliance on Salaried Developers === > > > > > > > > > > > > > > > > > > Lxin invested in lxdb as the solution and some of its key > engineers > > > > > > are working full time on the project. In addition, since there is a > > > > > > growing Big Data need for scalable solutions, we look forward to other > > > > > > Apache developers and researchers to contribute to the project. Also > key > > > > > > to addressing the risk associated with relying on Salaried developers > > > > > from > > > > > > a single entity is to increase the diversity of the contributors and > > > > > > actively lobby , Apache lxdb intends to do this. > > > > > > > > > > > > > > > > > > === An Excessive Fascination with the Apache Brand === > > > > > > > > > > > > > > > > > > Lxdb is proposing to enter incubation at Apache in order to help > efforts > > > > > > to diversify the committer-base, not so much to capitalize on the > Apache > > > > > > brand. The Lxdb project is in production use already inside lxdb, but > is > > > > > > not expected to be an lxdb product for external customers. As such, the > > > > > > lxdb project is not seeking to use the Apache brand as a marketing > tool. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > === Documentation=== > > > > > > > > > > > > > > > > > > Information about Palo can be found at > https://github.com/lucene-cn/lxdb > > > > > . > > > > > > The following links provide more information about lxdb in open source: > > > > > > > > > > > > > > > > > > * wiki site: https://github.com/lucene-cn/lxdb/wiki > > > > > > * Issue Tracking: https://github.com/lucene-cn/lxdb/issues > > > > > > * Overview: https://github.com/lucene-cn/lxdb/wiki/intro > > > > > > * lxin home page: http://www.lucene.xin > > > > > > > > > > > > * lsql document: http://docs.lucene.xin/lsql/v21/ > > > > > > > > > > > > > > > > > > > > > > > > ##Initial Source > > > > > > > > > > > > > > > > > > lxdb will development source code under an Apache license at > > > > > > https://github.com/lucene-cn/lxdb. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > === Core Developers === > > > > > > > > > > > > > > > > > > > > > > > > Currently most of the core developers of LXDB are working in the > research > > > > > > Team of luxin. > > > > > > > > > > > > > > > > > > - yannian mu (dev) > > > > > > - yu chen (dev) > > > > > > - guangshi hao (dev) > > > > > > - wei sun (dev) > > > > > > - qihua zheng (dev) > > > > > > - xin wang (dev) > > > > > > - qingsong liu (dev) > > > > > > - anxing zhou (Tester) > > > > > > - jiajun duan (Tester) > > > > > > > > > > > > > > > > > > > > > > > > == External Dependencies == > > > > > > > > > > > > As all dependencies are managed using Apache Maven > > > > > > Dependency License > > > > > > > Optional? > > > > > > lucene Apache License 2.0 > > > > > > true > > > > > > zookeeper Apache License > > > > > 2.0 > > > > > > true > > > > > > hbase Apache License 2.0 > > > > > > true > > > > > > spark Apache License 2.0 > > > > > > true > > > > > > hadoop Apache > > > > > > License 2.0 true > > > > > > hive Apache License 2.0 > > > > > true > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > == Required Resources == > > > > > > > > > > > > > > > > > > === Mailing lists === > > > > > > > > > > > > > > > > > > * lxdb-private (PMC discussion) > > > > > > * lxdb-dev (developer discussion) > > > > > > * lxdb-user (user discussion) > > > > > > * lxdb-commits (SCM commits) > > > > > > * lxdb-issues (JIRA issue feed) > > > > > > > > > > > > > > > > > > === Subversion Directory === > > > > > > > > > > > > > > > > > > Instead of subversion, LXDB prefers to git as source control > > > > > > management system: git://git.apache.org/lxdb > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > Sent from: http://apache-incubator-general.996316.n3.nabble.com/ > > > > > > > > > > --------------------------------------------------------------------- > > > > > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > > > > > For additional commands, e-mail: general-h...@incubator.apache.org > > > > > > > > > > > > >
