Sending the data again, I hope this is makes it clearer. I do not mind sharing the source, assuming you just want the code that does the creating, deleting etc of nodes (attached) How I created the Document stores is in the previous email, but if you want I can send that also.
*All milliseconds...* Oak: Create 1000 (Mysql,PostGress,Mongo) 3444,2483,8497 Query 1000 (Mysql,PostGress,Mongo) 2,19,2 Upload 100 files (Mysql,PostGress,Mongo) 1455,1130,845 Move 1000 (Mysql,PostGress,Mongo) 96349,2404,14428 Copied 1000 (Mysql,PostGress,Mongo) 2246,556,4432 Delete 1000 (Mysql,PostGress,Mongo) 92923,1523,7667 Update 1000 (Mysql,PostGress,Mongo) 48647,1055,4640 Read 1000 (Mysql,PostGress,Mongo) 98,111,142 Jackrabbit 2: Create 1000 (Mysql) 3022 Query 1000 (Mysql) 143 Upload 100 files (Mysql) 1105 Move 1000 (Mysql) 16 Copied 1000 (Mysql) 764 Delete 1000 (Mysql) 1481 Update 1000 (Mysql) 1139 Read 1000 (Mysql) 12 Oak: Create 10000 (Mysql,PostGress,Mongo) 31250,16475,342192 Query 10000 (Mysql,PostGress,Mongo) 4,16,2 Upload 100 files (Mysql,PostGress,Mongo) 1146,605,753 Move 10000 (Mysql,PostGress,Mongo) 741474,30339,406259 Copied 10000 (Mysql,PostGress,Mongo) 20755,7615,43670 Delete 10000 (Mysql,PostGress,Mongo) 728737,24461,43670 Update 10000 (Mysql,PostGress,Mongo) 374387,12453,41053 Read 10000 (Mysql,PostGress,Mongo) 2216,2989,968 Jackrabbit 2: Create 10000 (Mysql) 8507 Query 10000 (Mysql) 94 Upload 1000 files (Mysql) 744 Move 10000 (Mysql) 14 Copied 10000 (Mysql) 489 Delete 10000 (Mysql) 824 Update 10000 (Mysql) 987 Read 10000 (Mysql) 8 On Tue, Mar 29, 2016 at 8:28 AM, Marcel Reutegger <[email protected]> wrote: > Hi Domenic, > > the number of test cases do not match the results you > provided. i.e. the column headers do not match data > columns. can you please clarify how the results map > to the test cases? > > also, do you mind sharing the test code? I'd like to > better understand what the tests do. > > Regards > Marcel > > On 29/03/16 14:04, "Domenic DiTano" wrote: > > >Sorry those images did not come through, posting the email again with the > >raw data: > > > >I work with web application that has Jackrabbit 2.10 embedded and we > >wanted to try upgrading to Oak. Our current configuration that we use for > >Jackrabbit 2.10 is the FileDataStore along with MySql for the Persistence > >DataStore. We wrote some test cases to measure the performance of > >JackRabbit 2.1.0 vs latest Oak 1.2. In the case of JackRabbit 2.10, we > >used what our current application configuration - FileDataStore along with > >MySql. In the case of Oak we tried many configurations but the one we > >settled on was a DocumentNodeStore with a FileDataStore backend. We tried > >all 3 RDB options (Mongo, PostGress, MySql). All Test cases used the same > >code which standard JCR 2.0 code. The test cases did the following: > > > >. create 1000 & 10,000 nodes > >. move 1000 & 10,000 nodes > >. copy 1000 & 10,000 nodes > >. delete 1000 & 10,000 nodes > >. upload 100 files > >. read 1 property on 1000 & 10,000 nodes > >. update 1 property on 1000 & 10,000 nodes > > > > > >The results were as follows (all results in milliseconds): > > > >Oak tests ran with the creation, move, copy, delete, update, and read of > >1000 nodes: > > > >Create 1000 Nodes,Query Properties,Upload 100,Move 1000,Copied 1000,Delete > >1000 > >MySql:3444,2,1445,96349,2246,92923,48647,98 > >Postgress:2483,19,1130,2404,556,1523,1055,111 > >Mongo:8497,2,845,14428,4432,7667,4640,142 > > > >Postgress seems to perform well overall. > > > >In the case of Jackrabbit 2.10 (tests ran with the creation, move, copy, > >delete, update, and read of 1000 nodes): > >Create 1000 Nodes,Query Properties,Upload 100,Move 1000,Copied 1000,Delete > >1000 > >MySql:3022,143,1105,16,764,1481,1139,12 > > > > > >Jackrabbit 2.10 performs slightly better than Oak. > > > >The next set of tests were ran with Oak with the creation, move, copy, > >delete, update, and read of 10000 nodes: > > > >Create 10000 Nodes,Query Properties,Upload 100,Move 10000,Copied > >10000,Delete 10000,Update 10000,Read 10000 > >MySql:31250,4,1146,741474,20755,728737,374387,2216 > >Postgress:16475,16,605,30339,7615,24461,12453,2989 > >Mongo:342192,2,753,406259,321040,43670,41053,968 > > > >Postgress once again performed ok. Mongo and MySql did not do well around > >Moves, deletes, and updates. Querying did well also as indexes were > >created. > > > >In the case of Jackrabbit 2.10 (tests ran with the creation, move, copy, > >delete, update, and read of 10000 nodes): > >Create 10000 Nodes,Query Properties,Upload 100,Move 10000,Copied > >10000,Delete 10000,Update 10000,Read 10000 > >MySql:8507,94,744,14,489,824,987,8 > > > >Jackrabbit 2.10 performed much better than Oak in general. > > > >Based on the results I have a few questions/comments: > > > >. Are these fair comparisons between Jackrabbit and Oak? In our > >application it is very possible to create 1-10,000 nodes in a user > >session. > >. Should I have assumed Oak would outperform Jackrabbit 2.10? > >. I understand MySql is experimental but Mongo is not - I would > >assume Mongo would perform as well if not better than Postgress > >. The performance bottlenecks seem to be at the JDBC level for > >MySql. I made some configuration changes which helped performance but the > >changes would make MySql fail any ACID tests. > > > >Just a few notes: > > > >The same JCR code was used for creating, moving, deleting etc any nodes. > >The JCR code was used for all the tests. The tests were all run on the > >same machine > > > >Used DocumentMK Builder for all DataStores: > > > >Mongo: > > DocumentNodeStore storeD = new > >DocumentMK.Builder().setPersistentCache("D:\\ekm-oak\\Mongo,size=1024,bina > >ry=0").setMongoDB(db).setBlobStore(new > >DataStoreBlobStore(fds)).getNodeStore(); > > > >MySql: > > RDBOptions options = new > >RDBOptions().tablePrefix(prefix).dropTablesOnClose(false); > > DocumentNodeStore storeD = new > >DocumentMK.Builder().setBlobStore(new > >DataStoreBlobStore(fds)).setClusterId(1).memoryCacheSize(64 * 1024 * > >1024). > > > >setPersistentCache("D:\\ekm-oak\\MySql,size=1024,binary=0").setRDBConnecti > >on(RDBDataSourceFactory.forJdbcUrl(url, userName, password), > >options).getNodeStore(); > >PostGres: > > RDBOptions options = new > >RDBOptions().tablePrefix(prefix).dropTablesOnClose(false); > > DocumentNodeStore storeD = new > >DocumentMK.Builder().setAsyncDelay(0).setBlobStore(new > >DataStoreBlobStore(fds)).setClusterId(1).memoryCacheSize(64 * 1024 * > >1024). > > > >setPersistentCache("D:\\ekm-oak\\postGress,size=1024,binary=0").setRDBConn > >ection(RDBDataSourceFactory.forJdbcUrl(url, userName, password), > >options).getNodeStore(); > > > >The repository was created the same for all three: > >Repository repository = new Jcr(new Oak(storeD)).with(new > >LuceneIndexEditorProvider()).with(configureSearch()).createRepository(); > > > >Any input is welcome.. > > > >Thanks, > >Domenic > > > >-----Original Message----- > >From: Marcel Reutegger [mailto:[email protected]] > >Sent: Tuesday, March 29, 2016 4:41 AM > >To: [email protected] > >Subject: Re: Jackrabbit 2.10 vs Oak 1.2.7 > > > >Hi, > > > >the graphs didn't make it through to the mailing list. > >Can you please post raw numbers or a link to the graphs? > > > >Without access to more data, my guess is that Oak on DocumentNodeStore is > >slower with the bigger changes set because it internally creates a branch > >to stage changes when it reaches a given threshold. This introduces more > >traffic to the backend storage when save() is called, because previously > >written data is retrieved again from the backend. > > > >Jackrabbit 2.10 on the other hand keeps the entire changes in memory until > >save() is called. > > > >You can increase the threshold for the DocumentNodeStore with a system > >property: -Dupdate.limit=100000 > > > >The default is 10'000. > > > >Regards > > Marcel > > > >On 29/03/16 04:19, "Domenic DiTano" wrote: > > > >>Hello, > >> > >>I work with web application that has Jackrabbit 2.10 embedded and we > >>wanted to try upgrading to Oak. Our current configuration that we use > >>for Jackrabbit > >>2.10 is the FileDataStore along with MySql for the Persistence DataStore. > >> We wrote some test cases to measure the performance of JackRabbit > >>2.1.0 vs latest Oak 1.2. In the case of JackRabbit 2.10, we used what > >>our current application configuration FileDataStore along with MySql. > >>In the case of Oak we tried many configurations but the one we settled > >>on was a DocumentNodeStore with a FileDataStore backend.We tried all 3 > >>RDB options (Mongo, PostGress, MySql). > >>All Test cases used the same code which standard > >>JCR 2.0 code. The test cases did the following: > >> > >>. > >>create 1000 & 10,000 nodes > >>. > >>move 1000 & 10,000 nodes > >>. > >>copy 1000 & 10,000 nodes > >>. > >>delete 1000 & 10,000 nodes > >>. > >>upload 100 files > >>. > >>read 1 property on 1000 & 10,000 nodes > >>. > >>update 1 property on 1000 & 10,000 nodes > >> > >> > >>The results were as follows (all results in milliseconds): > >> > >>Oak tests ran with the creation, move, copy, delete, update, and read > >>of > >>1000 nodes: > >> > >> > >> > >>Postgress seems to perform well overall. > >> > >>In the case of Jackrabbit 2.10 (tests ran with the creation, move, > >>copy, delete, update, and read of 1000 nodes): > >> > >> > >> > >>Jackrabbit 2.10 performs slightly better than Oak. > >> > >>The next set of tests were ran with Oak with the creation, move, copy, > >>delete, update, and read of 10000 nodes: > >> > >> > >> > >>Postgress once again performed ok. Mongo and MySql did not do well > >>around Moves, deletes, and updates. Querying did well also as indexes > >>were created. > >> > >>In the case of Jackrabbit 2.10 (tests ran with the creation, move, > >>copy, delete, update, and read of 10000 nodes): > >> > >> > >> > >>Jackrabbit 2.10 performed much > >>better than Oak in general. > >> > >>Based on the results I have a few questions/comments: > >> > >>. > >>Are these fair comparisons between Jackrabbit and Oak? In our > >>application it is very possible to create 1-10,000 nodes in a user > >>session. > >>. > >>Should I have assumed Oak would outperform Jackrabbit 2.10? > >>. > >>I understand MySql is experimental but Mongo is not I would assume > >>Mongo would perform as well if not better than Postgress > >>. > >>The performance bottlenecks seem to be at the JDBC level for MySql. I > >>made some configuration changes which helped performance but the > >>changes would make MySql fail any ACID tests. > >> > >>Just a few notes: > >> > >>The same JCR code was used for creating, moving, deleting etc any nodes. > >>The JCR code was used for all the tests. The tests were all run on the > >>same machine > >> > >>Used DocumentMK Builder for all DataStores: > >> > >>Mongo: > >> DocumentNodeStore storeD = new > >>DocumentMK.Builder().setPersistentCache("D:\\ekm-oak\\Mongo,size=1024,b > >>ina > >>ry=0").setMongoDB(db).setBlobStore(new > >>DataStoreBlobStore(fds)).getNodeStore(); > >> > >>MySql: > >> RDBOptions options = new > >>RDBOptions().tablePrefix(prefix).dropTablesOnClose(false); > >> DocumentNodeStore storeD = new > >>DocumentMK.Builder().setBlobStore(new > >>DataStoreBlobStore(fds)).setClusterId(1).memoryCacheSize(64 * 1024 * > >>1024). > >> > >>setPersistentCache("D:\\ekm-oak\\MySql,size=1024,binary=0").setRDBConne > >>cti on(RDBDataSourceFactory.forJdbcUrl(url, userName, password), > >>options).getNodeStore(); > >>PostGres: > >> RDBOptions options = new > >>RDBOptions().tablePrefix(prefix).dropTablesOnClose(false); > >> DocumentNodeStore storeD = new > >>DocumentMK.Builder().setAsyncDelay(0).setBlobStore(new > >>DataStoreBlobStore(fds)).setClusterId(1).memoryCacheSize(64 * 1024 * > >>1024). > >> > >>setPersistentCache("D:\\ekm-oak\\postGress,size=1024,binary=0").setRDBC > >>onn ection(RDBDataSourceFactory.forJdbcUrl(url, userName, password), > >>options).getNodeStore(); > >> > >>The repository was created the same for all three: > >>Repository repository = new Jcr(new Oak(storeD)).with(new > >>LuceneIndexEditorProvider()).with(configureSearch()).createRepository() > >>; > >> > >>Any input is welcomeŠ. > >> > >>Thanks, > >>Domenic > >> > >> > > -- Domenic DiTano ANSYS, Inc. Tel: 1.724.514.3624 [email protected] www.ansys.com
