BTW. I always understood that Hbase is append only. is that generally true?
thx Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* http://talebzadehmich.wordpress.com *Disclaimer:* Use it at your own risk. Any and all responsibility for any loss, damage or destruction of data or any other property which may arise from relying on this email's technical content is explicitly disclaimed. The author will in no case be liable for any monetary damages arising from such loss, damage or destruction. On 21 October 2016 at 21:57, Mich Talebzadeh <mich.talebza...@gmail.com> wrote: > agreed much like any rdbms > > > > Dr Mich Talebzadeh > > > > LinkedIn * > https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw > <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* > > > > http://talebzadehmich.wordpress.com > > > *Disclaimer:* Use it at your own risk. Any and all responsibility for any > loss, damage or destruction of data or any other property which may arise > from relying on this email's technical content is explicitly disclaimed. > The author will in no case be liable for any monetary damages arising from > such loss, damage or destruction. > > > > On 21 October 2016 at 21:54, Ted Yu <yuzhih...@gmail.com> wrote: > >> Well, updates (in memory) would ultimately be flushed to disk, resulting >> in >> new hfiles. >> >> On Fri, Oct 21, 2016 at 1:50 PM, Mich Talebzadeh < >> mich.talebza...@gmail.com> >> wrote: >> >> > thanks >> > >> > bq. all updates are done in memory o disk access >> > >> > I meant data updates are operated in memory, no disk access. >> > >> > in other much like rdbms read data into memory and update it there >> > (assuming that data is not already in memory?) >> > >> > HTH >> > >> > Dr Mich Talebzadeh >> > >> > >> > >> > LinkedIn * https://www.linkedin.com/profile/view?id= >> > AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw >> > <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrb >> Jd6zP6AcPCCd >> > OABUrV8Pw>* >> > >> > >> > >> > http://talebzadehmich.wordpress.com >> > >> > >> > *Disclaimer:* Use it at your own risk. Any and all responsibility for >> any >> > loss, damage or destruction of data or any other property which may >> arise >> > from relying on this email's technical content is explicitly disclaimed. >> > The author will in no case be liable for any monetary damages arising >> from >> > such loss, damage or destruction. >> > >> > >> > >> > On 21 October 2016 at 21:46, Ted Yu <yuzhih...@gmail.com> wrote: >> > >> > > bq. this search is carried out through map-reduce on region servers? >> > > >> > > No map-reduce. region server uses its own thread(s). >> > > >> > > bq. all updates are done in memory o disk access >> > > >> > > Can you clarify ? There seems to be some missing letters. >> > > >> > > On Fri, Oct 21, 2016 at 1:43 PM, Mich Talebzadeh < >> > > mich.talebza...@gmail.com> >> > > wrote: >> > > >> > > > thanks >> > > > >> > > > having read the docs it appears to me that the main reason of hbase >> > being >> > > > faster is: >> > > > >> > > > >> > > > 1. it behaves like an rdbms like oracle tetc. reads are looked >> for >> > in >> > > > the buffer cache for consistent reads and if not found then store >> > > files >> > > > on >> > > > disks are searched. Does this mean that this search is carried >> out >> > > > through >> > > > map-reduce on region servers? >> > > > 2. when the data is written it is written to log file >> sequentially >> > > > first, then to in-memory store, sorted like b-tree of rdbms and >> then >> > > > flushed to disk. this is exactly what checkpoint in an rdbms does >> > > > 3. one can point out that hbase is faster because log structured >> > merge >> > > > tree (LSM-trees) has less depth than a B-tree in rdbms. >> > > > 4. all updates are done in memory o disk access >> > > > 5. in summary LSM-trees reduce disk access when data is read from >> > disk >> > > > because of reduced seek time again less depth to get data with >> > > LSM-tree >> > > > >> > > > >> > > > appreciate any comments >> > > > >> > > > >> > > > cheers >> > > > >> > > > >> > > > Dr Mich Talebzadeh >> > > > >> > > > >> > > > >> > > > LinkedIn * https://www.linkedin.com/profile/view?id= >> > > > AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw >> > > > <https://www.linkedin.com/profile/view?id= >> > AAEAAAAWh2gBxianrbJd6zP6AcPCCd >> > > > OABUrV8Pw>* >> > > > >> > > > >> > > > >> > > > http://talebzadehmich.wordpress.com >> > > > >> > > > >> > > > *Disclaimer:* Use it at your own risk. Any and all responsibility >> for >> > any >> > > > loss, damage or destruction of data or any other property which may >> > arise >> > > > from relying on this email's technical content is explicitly >> > disclaimed. >> > > > The author will in no case be liable for any monetary damages >> arising >> > > from >> > > > such loss, damage or destruction. >> > > > >> > > > >> > > > >> > > > On 21 October 2016 at 17:51, Ted Yu <yuzhih...@gmail.com> wrote: >> > > > >> > > > > See some prior blog: >> > > > > >> > > > > http://www.cyanny.com/2014/03/13/hbase-architecture- >> > > > > analysis-part1-logical-architecture/ >> > > > > >> > > > > w.r.t. compaction in Hive, it is used to compact deltas into a >> base >> > > file >> > > > > (in the context of transactions). Likely they're different. >> > > > > >> > > > > Cheers >> > > > > >> > > > > On Fri, Oct 21, 2016 at 9:08 AM, Mich Talebzadeh < >> > > > > mich.talebza...@gmail.com> >> > > > > wrote: >> > > > > >> > > > > > Hi, >> > > > > > >> > > > > > Can someone in a nutshell explain *the *Hbase use of >> log-structured >> > > > > > merge-tree (LSM-tree) as data storage architecture >> > > > > > >> > > > > > The idea of merging smaller files to larger files periodically >> to >> > > > reduce >> > > > > > disk seeks, is this similar concept to compaction in HDFS or >> Hive? >> > > > > > >> > > > > > Thanks >> > > > > > >> > > > > > >> > > > > > Dr Mich Talebzadeh >> > > > > > >> > > > > > >> > > > > > >> > > > > > LinkedIn * https://www.linkedin.com/profile/view?id= >> > > > > > AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw >> > > > > > <https://www.linkedin.com/profile/view?id= >> > > > AAEAAAAWh2gBxianrbJd6zP6AcPCCd >> > > > > > OABUrV8Pw>* >> > > > > > >> > > > > > >> > > > > > >> > > > > > http://talebzadehmich.wordpress.com >> > > > > > >> > > > > > >> > > > > > *Disclaimer:* Use it at your own risk. Any and all >> responsibility >> > for >> > > > any >> > > > > > loss, damage or destruction of data or any other property which >> may >> > > > arise >> > > > > > from relying on this email's technical content is explicitly >> > > > disclaimed. >> > > > > > The author will in no case be liable for any monetary damages >> > arising >> > > > > from >> > > > > > such loss, damage or destruction. >> > > > > > >> > > > > > >> > > > > > >> > > > > > On 21 October 2016 at 15:27, Mich Talebzadeh < >> > > > mich.talebza...@gmail.com> >> > > > > > wrote: >> > > > > > >> > > > > > > Sorry that should read Hive not Spark here >> > > > > > > >> > > > > > > Say compared to Spark that is basically a SQL layer relying on >> > > > > different >> > > > > > > engines (mr, Tez, Spark) to execute the code >> > > > > > > >> > > > > > > Dr Mich Talebzadeh >> > > > > > > >> > > > > > > >> > > > > > > >> > > > > > > LinkedIn * https://www.linkedin.com/profile/view?id= >> > > > > > AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw >> > > > > > > <https://www.linkedin.com/profile/view?id= >> > > > > AAEAAAAWh2gBxianrbJd6zP6AcPCCd >> > > > > > OABUrV8Pw>* >> > > > > > > >> > > > > > > >> > > > > > > >> > > > > > > http://talebzadehmich.wordpress.com >> > > > > > > >> > > > > > > >> > > > > > > *Disclaimer:* Use it at your own risk. Any and all >> responsibility >> > > for >> > > > > any >> > > > > > > loss, damage or destruction of data or any other property >> which >> > may >> > > > > arise >> > > > > > > from relying on this email's technical content is explicitly >> > > > > disclaimed. >> > > > > > > The author will in no case be liable for any monetary damages >> > > arising >> > > > > > from >> > > > > > > such loss, damage or destruction. >> > > > > > > >> > > > > > > >> > > > > > > >> > > > > > > On 21 October 2016 at 13:17, Ted Yu <yuzhih...@gmail.com> >> wrote: >> > > > > > > >> > > > > > >> Mich: >> > > > > > >> Here is brief description of hbase architecture: >> > > > > > >> https://hbase.apache.org/book.html#arch.overview >> > > > > > >> >> > > > > > >> You can also get more details from Lars George's or Nick >> > Dimiduk's >> > > > > > books. >> > > > > > >> >> > > > > > >> HBase doesn't support SQL directly. There is no cost based >> > > > > optimization. >> > > > > > >> >> > > > > > >> Cheers >> > > > > > >> >> > > > > > >> > On Oct 21, 2016, at 1:43 AM, Mich Talebzadeh < >> > > > > > mich.talebza...@gmail.com> >> > > > > > >> wrote: >> > > > > > >> > >> > > > > > >> > Hi, >> > > > > > >> > >> > > > > > >> > This is a general question. >> > > > > > >> > >> > > > > > >> > Is Hbase fast because Hbase uses Hash tables and provides >> > random >> > > > > > access, >> > > > > > >> > and it stores the data in indexed HDFS files for faster >> > lookups. >> > > > > > >> > >> > > > > > >> > Say compared to Spark that is basically a SQL layer >> relying on >> > > > > > different >> > > > > > >> > engines (mr, Tez, Spark) to execute the code (although it >> has >> > > Cost >> > > > > > Base >> > > > > > >> > Optimizer), how Hbase fares, beyond relying on these >> engines >> > > > > > >> > >> > > > > > >> > Thanks >> > > > > > >> > >> > > > > > >> > >> > > > > > >> > Dr Mich Talebzadeh >> > > > > > >> > >> > > > > > >> > >> > > > > > >> > >> > > > > > >> > LinkedIn * https://www.linkedin.com/profile/view?id= >> > > > > > AAEAAAAWh2gBxianrbJ >> > > > > > >> d6zP6AcPCCdOABUrV8Pw >> > > > > > >> > <https://www.linkedin.com/prof >> ile/view?id=AAEAAAAWh2gBxianrb >> > > > > > >> Jd6zP6AcPCCdOABUrV8Pw>* >> > > > > > >> > >> > > > > > >> > >> > > > > > >> > >> > > > > > >> > http://talebzadehmich.wordpress.com >> > > > > > >> > >> > > > > > >> > >> > > > > > >> > *Disclaimer:* Use it at your own risk. Any and all >> > > responsibility >> > > > > for >> > > > > > >> any >> > > > > > >> > loss, damage or destruction of data or any other property >> > which >> > > > may >> > > > > > >> arise >> > > > > > >> > from relying on this email's technical content is >> explicitly >> > > > > > disclaimed. >> > > > > > >> > The author will in no case be liable for any monetary >> damages >> > > > > arising >> > > > > > >> from >> > > > > > >> > such loss, damage or destruction. >> > > > > > >> >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> > >
