Hi *be*njamin, How stable is Kudu?
Is it production ready? Thanks 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 3 October 2016 at 18:08, Benjamin Kim <bbuil...@gmail.com> wrote: > If you’re interested, here is the link to the development page for Kudu. > It has the Spark code snippets using DataFrames. > > http://kudu.apache.org/docs/developing.html > > Cheers, > Ben > > On Oct 3, 2016, at 9:56 AM, ayan guha <guha.a...@gmail.com> wrote: > > That sounds interesting, would love to learn more about it. > > Mitch: looks good. Lastly I would suggest you to think if you really need > multiple column families. > On 4 Oct 2016 02:57, "Benjamin Kim" <bbuil...@gmail.com> wrote: > >> Lately, I’ve been experimenting with Kudu. It has been a much better >> experience than with HBase. Using it is much simpler, even from spark-shell. >> >> spark-shell --packages org.apache.kudu:kudu-spark_2.10:1.0.0 >> >> It’s like going back to rudimentary DB systems where tables have just a >> primary key and the columns. Additional benefits include a home-grown spark >> package, fast upserts and table scans for analytics, time-series support >> just introduced, and (my favorite) simpler configuration and >> administration. It has just gone to version 1.0.0; so, I’m waiting for >> 1.0.1+ before I propose it as our HBase replacement for some bugs to shake >> out. All my performance tests have been stellar versus HBase especially >> with its simplicity. >> >> Just a thought… >> >> Cheers, >> Ben >> >> >> On Oct 3, 2016, at 8:40 AM, Mich Talebzadeh <mich.talebza...@gmail.com> >> wrote: >> >> Hi, >> >> I decided to create a composite key *ticker-date* from the csv file >> >> I just did some manipulation on CSV file >> >> export IFS=",";sed -i 1d tsco.csv; cat tsco.csv | while read a b c d e f; >> do echo "TSCO-$a,TESCO PLC,TSCO,$a,$b,$c,$d,$e,$f"; done > temp; mv -f temp >> tsco.csv >> >> Which basically takes the csv file, tells the shell that field separator >> IFS=",", drops the header, reads every field in every line (1,b,c ..), >> creates the composite key TSCO-$a, adds the stock name and ticker to the >> csv file. The whole process can be automated and parameterised. >> >> Once the csv file is put into HDFS then, I run the following command >> >> $HBASE_HOME/bin/hbase org.apache.hadoop.hbase.mapreduce.ImportTsv >> -Dimporttsv.separator=',' -Dimporttsv.columns="HBASE_ROW >> _KEY,stock_info:stock,stock_info:ticker,stock_daily:Date,sto >> ck_daily:open,stock_daily:high,stock_daily:low,stock_daily:c >> lose,stock_daily:volume" tsco hdfs://rhes564:9000/data/stocks/tsco.csv >> >> The Hbase table is created as below >> >> create 'tsco','stock_info','stock_daily' >> >> and this is the data (2 rows each 2 family and with 8 attributes) >> >> hbase(main):132:0> scan 'tsco', LIMIT => 2 >> ROW COLUMN+CELL >> TSCO-1-Apr-08 >> column=stock_daily:Date, timestamp=1475507091676, value=1-Apr-08 >> TSCO-1-Apr-08 >> column=stock_daily:close, timestamp=1475507091676, value=405.25 >> TSCO-1-Apr-08 >> column=stock_daily:high, timestamp=1475507091676, value=406.75 >> TSCO-1-Apr-08 >> column=stock_daily:low, timestamp=1475507091676, value=379.25 >> TSCO-1-Apr-08 >> column=stock_daily:open, timestamp=1475507091676, value=380.00 >> TSCO-1-Apr-08 >> column=stock_daily:volume, timestamp=1475507091676, value=49664486 >> TSCO-1-Apr-08 >> column=stock_info:stock, timestamp=1475507091676, value=TESCO PLC >> TSCO-1-Apr-08 >> column=stock_info:ticker, timestamp=1475507091676, value=TSCO >> >> TSCO-1-Apr-09 >> column=stock_daily:Date, timestamp=1475507091676, value=1-Apr-09 >> TSCO-1-Apr-09 >> column=stock_daily:close, timestamp=1475507091676, value=333.30 >> TSCO-1-Apr-09 >> column=stock_daily:high, timestamp=1475507091676, value=334.60 >> TSCO-1-Apr-09 >> column=stock_daily:low, timestamp=1475507091676, value=326.50 >> TSCO-1-Apr-09 >> column=stock_daily:open, timestamp=1475507091676, value=331.10 >> TSCO-1-Apr-09 >> column=stock_daily:volume, timestamp=1475507091676, value=24877341 >> TSCO-1-Apr-09 >> column=stock_info:stock, timestamp=1475507091676, value=TESCO PLC >> TSCO-1-Apr-09 >> column=stock_info:ticker, timestamp=1475507091676, value=TSCO >> >> Any suggestions >> >> Thanks >> >> 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 3 October 2016 at 14:42, Mich Talebzadeh <mich.talebza...@gmail.com> >> wrote: >> >>> or may be add ticker+date like similar >>> >>> >>> <image.png> >>> >>> So the new row key would be TSCO-1-Apr-08 >>> >>> and this will be added as row key. Both Date and ticker will stay as >>> they are as column family attributes? >>> >>> >>> >>> 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 3 October 2016 at 14:32, Mich Talebzadeh <mich.talebza...@gmail.com> >>> wrote: >>> >>>> with ticker+date I can c reate something like below for row key >>>> >>>> TSCO_1-Apr-08 >>>> >>>> >>>> or TSCO1-Apr-08 >>>> >>>> if I understood you correctly >>>> >>>> >>>> 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 3 October 2016 at 13:13, ayan guha <guha.a...@gmail.com> wrote: >>>> >>>>> Hi >>>>> >>>>> Looks like you are saving to new.csv but still loading tsco.csv? Its >>>>> definitely the header. >>>>> >>>>> Suggestion: ticker+date as row key has following benefits: >>>>> >>>>> 1. using ticker+date as row key will enable you to hold multiple >>>>> ticker in this single hbase table. (Think composite primary key) >>>>> 2. Using date itself as row key will lead to hotspots (Look up >>>>> hotspoting due to monotonically increasing row key). To distribute the >>>>> load, it is suggested to use a salting. Ticker can be used as a natural >>>>> salt in this case. >>>>> 3. Also, you may want to hash the rowkey value to give it little more >>>>> flexible (Think surrogate key). >>>>> >>>>> >>>>> >>>>> On Mon, Oct 3, 2016 at 10:17 PM, Mich Talebzadeh <mich.talebzadeh@ >>>>> gmail.com> wrote: >>>>> >>>>>> Hi Ayan, >>>>>> >>>>>> Sounds like the row key has to be unique much like a primary key in >>>>>> RDBMS >>>>>> >>>>>> This is what I download as a csv for stock from Google Finance >>>>>> >>>>>> Date Open High Low Close Volume >>>>>> 27-Sep-16 177.4 177.75 172.5 177.75 24117196 >>>>>> >>>>>> >>>>>> So What I do I add the stock and ticker myself to end of the row via >>>>>> shell script and get rid of header >>>>>> >>>>>> sed -i 1d tsco.csv; cat tsco.csv|awk '{print $0,",TESCO PLC,TSCO"}' > >>>>>> new.csv >>>>>> >>>>>> The New table has two column families: stock_price, stock_info and >>>>>> row key date (one row per date) >>>>>> >>>>>> This creates a new csv file with two additional columns appended to >>>>>> the end of each line >>>>>> >>>>>> Then I run the following command >>>>>> >>>>>> $HBASE_HOME/bin/hbase org.apache.hadoop.hbase.mapreduce.ImportTsv >>>>>> -Dimporttsv.separator=',' -Dimporttsv.columns="HBASE_ROW_KEY, >>>>>> stock_daily:open, stock_daily:high, stock_daily:low, stock_daily:close, >>>>>> stock_daily:volume, stock_info:stock, stock_info:ticker" tsco >>>>>> hdfs://rhes564:9000/data/stocks/tsco.csv >>>>>> >>>>>> This is in Hbase table for a given day >>>>>> >>>>>> hbase(main):090:0> scan 'tsco', LIMIT => 10 >>>>>> ROW COLUMN+CELL >>>>>> 1-Apr-08 >>>>>> column=stock_daily:close, timestamp=1475492248665, value=405.25 >>>>>> 1-Apr-08 >>>>>> column=stock_daily:high, timestamp=1475492248665, value=406.75 >>>>>> 1-Apr-08 >>>>>> column=stock_daily:low, timestamp=1475492248665, value=379.25 >>>>>> 1-Apr-08 >>>>>> column=stock_daily:open, timestamp=1475492248665, value=380.00 >>>>>> 1-Apr-08 >>>>>> column=stock_daily:volume, timestamp=1475492248665, value=49664486 >>>>>> 1-Apr-08 >>>>>> column=stock_info:stock, timestamp=1475492248665, value=TESCO PLC >>>>>> 1-Apr-08 >>>>>> column=stock_info:ticker, timestamp=1475492248665, value=TSCO >>>>>> >>>>>> >>>>>> But I also have this at the bottom >>>>>> >>>>>> Date >>>>>> column=stock_daily:close, timestamp=1475491189158, value=Close >>>>>> Date >>>>>> column=stock_daily:high, timestamp=1475491189158, value=High >>>>>> Date >>>>>> column=stock_daily:low, timestamp=1475491189158, value=Low >>>>>> Date >>>>>> column=stock_daily:open, timestamp=1475491189158, value=Open >>>>>> Date >>>>>> column=stock_daily:volume, timestamp=1475491189158, value=Volume >>>>>> Date >>>>>> column=stock_info:stock, timestamp=1475491189158, value=TESCO PLC >>>>>> Date >>>>>> column=stock_info:ticker, timestamp=1475491189158, value=TSCO >>>>>> >>>>>> Sounds like the table header? >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> 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 3 October 2016 at 11:24, ayan guha <guha.a...@gmail.com> wrote: >>>>>> >>>>>>> I am not well versed with importtsv, but you can create a CSV file >>>>>>> using a simple spark program to create first column as >>>>>>> ticker+tradedate. I >>>>>>> remember doing similar manipulation to create row key format in pig. >>>>>>> >>>>>>> On 3 Oct 2016 20:40, "Mich Talebzadeh" <mich.talebza...@gmail.com> >>>>>>> wrote: >>>>>>> >>>>>>>> Thanks Ayan, >>>>>>>> >>>>>>>> How do you specify ticker+rtrade as row key in the below >>>>>>>> >>>>>>>> hbase org.apache.hadoop.hbase.mapreduce.ImportTsv >>>>>>>> -Dimporttsv.separator=',' -Dimporttsv.columns="HBASE_ROW_KEY, >>>>>>>> stock_daily:ticker, stock_daily:tradedate, >>>>>>>> stock_daily:open,stock_daily:h >>>>>>>> igh,stock_daily:low,stock_daily:close,stock_daily:volume" tsco >>>>>>>> hdfs://rhes564:9000/data/stocks/tsco.csv >>>>>>>> >>>>>>>> I always thought that Hbase will take the first column as row key >>>>>>>> so it takes stock as the row key which is tsco plc for every row! >>>>>>>> >>>>>>>> Does row key need to be unique? >>>>>>>> >>>>>>>> cheers >>>>>>>> >>>>>>>> >>>>>>>> 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 3 October 2016 at 10:30, ayan guha <guha.a...@gmail.com> wrote: >>>>>>>> >>>>>>>>> Hi Mitch >>>>>>>>> >>>>>>>>> It is more to do with hbase than spark. >>>>>>>>> >>>>>>>>> Row key can be anything, yes but essentially what you are doing is >>>>>>>>> insert and update tesco PLC row. Given your schema, ticker+trade date >>>>>>>>> seems >>>>>>>>> to be a good row key >>>>>>>>> On 3 Oct 2016 18:25, "Mich Talebzadeh" <mich.talebza...@gmail.com> >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> thanks again. >>>>>>>>>> >>>>>>>>>> I added that jar file to the classpath and that part worked. >>>>>>>>>> >>>>>>>>>> I was using spark shell so I have to use spark-submit for it to >>>>>>>>>> be able to interact with map-reduce job. >>>>>>>>>> >>>>>>>>>> BTW when I use the command line utility ImportTsv to load a file >>>>>>>>>> into Hbase with the following table format >>>>>>>>>> >>>>>>>>>> describe 'marketDataHbase' >>>>>>>>>> Table marketDataHbase is ENABLED >>>>>>>>>> marketDataHbase >>>>>>>>>> COLUMN FAMILIES DESCRIPTION >>>>>>>>>> {NAME => 'price_info', BLOOMFILTER => 'ROW', VERSIONS => '1', >>>>>>>>>> IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', >>>>>>>>>> DATA_BLOCK_ENCODING => >>>>>>>>>> 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERSIONS => >>>>>>>>>> '0', BLOCKC >>>>>>>>>> ACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'} >>>>>>>>>> 1 row(s) in 0.0930 seconds >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> hbase org.apache.hadoop.hbase.mapreduce.ImportTsv >>>>>>>>>> -Dimporttsv.separator=',' -Dimporttsv.columns="HBASE_ROW_KEY, >>>>>>>>>> stock_daily:ticker, stock_daily:tradedate, >>>>>>>>>> stock_daily:open,stock_daily:h >>>>>>>>>> igh,stock_daily:low,stock_daily:close,stock_daily:volume" tsco >>>>>>>>>> hdfs://rhes564:9000/data/stocks/tsco.csv >>>>>>>>>> >>>>>>>>>> There are with 1200 rows in the csv file,* but it only loads the >>>>>>>>>> first row!* >>>>>>>>>> >>>>>>>>>> scan 'tsco' >>>>>>>>>> ROW >>>>>>>>>> COLUMN+CELL >>>>>>>>>> Tesco PLC >>>>>>>>>> column=stock_daily:close, timestamp=1475447365118, value=325.25 >>>>>>>>>> Tesco PLC >>>>>>>>>> column=stock_daily:high, timestamp=1475447365118, value=332.00 >>>>>>>>>> Tesco PLC >>>>>>>>>> column=stock_daily:low, timestamp=1475447365118, value=324.00 >>>>>>>>>> Tesco PLC >>>>>>>>>> column=stock_daily:open, timestamp=1475447365118, value=331.75 >>>>>>>>>> Tesco PLC >>>>>>>>>> column=stock_daily:ticker, timestamp=1475447365118, value=TSCO >>>>>>>>>> Tesco PLC >>>>>>>>>> column=stock_daily:tradedate, timestamp=1475447365118, value= >>>>>>>>>> 3-Jan-06 >>>>>>>>>> Tesco PLC >>>>>>>>>> column=stock_daily:volume, timestamp=1475447365118, value=46935045 >>>>>>>>>> 1 row(s) in 0.0390 seconds >>>>>>>>>> >>>>>>>>>> Is this because the hbase_row_key --> Tesco PLC is the same for >>>>>>>>>> all? I thought that the row key can be anything. >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> 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 3 October 2016 at 07:44, Benjamin Kim <bbuil...@gmail.com> >>>>>>>>>> wrote: >>>>>>>>>> >>>>>>>>>>> We installed Apache Spark 1.6.0 at the time alongside CDH 5.4.8 >>>>>>>>>>> because Cloudera only had Spark 1.3.0 at the time, and we wanted to >>>>>>>>>>> use >>>>>>>>>>> Spark 1.6.0’s features. We borrowed the >>>>>>>>>>> /etc/spark/conf/spark-env.sh file >>>>>>>>>>> that Cloudera generated because it was customized to add jars first >>>>>>>>>>> from >>>>>>>>>>> paths listed in the file /etc/spark/conf/classpath.txt. So, we >>>>>>>>>>> entered the >>>>>>>>>>> path for the htrace jar into the /etc/spark/conf/classpath.txt >>>>>>>>>>> file. Then, >>>>>>>>>>> it worked. We could read/write to HBase. >>>>>>>>>>> >>>>>>>>>>> On Oct 2, 2016, at 12:52 AM, Mich Talebzadeh < >>>>>>>>>>> mich.talebza...@gmail.com> wrote: >>>>>>>>>>> >>>>>>>>>>> Thanks Ben >>>>>>>>>>> >>>>>>>>>>> The thing is I am using Spark 2 and no stack from CDH! >>>>>>>>>>> >>>>>>>>>>> Is this approach to reading/writing to Hbase specific to >>>>>>>>>>> Cloudera? >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> 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 1 October 2016 at 23:39, Benjamin Kim <bbuil...@gmail.com> >>>>>>>>>>> wrote: >>>>>>>>>>> >>>>>>>>>>>> Mich, >>>>>>>>>>>> >>>>>>>>>>>> I know up until CDH 5.4 we had to add the HTrace jar to the >>>>>>>>>>>> classpath to make it work using the command below. But after >>>>>>>>>>>> upgrading to >>>>>>>>>>>> CDH 5.7, it became unnecessary. >>>>>>>>>>>> >>>>>>>>>>>> echo "/opt/cloudera/parcels/CDH/jar >>>>>>>>>>>> s/htrace-core-3.2.0-incubating.jar" >> >>>>>>>>>>>> /etc/spark/conf/classpath.txt >>>>>>>>>>>> >>>>>>>>>>>> Hope this helps. >>>>>>>>>>>> >>>>>>>>>>>> Cheers, >>>>>>>>>>>> Ben >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On Oct 1, 2016, at 3:22 PM, Mich Talebzadeh < >>>>>>>>>>>> mich.talebza...@gmail.com> wrote: >>>>>>>>>>>> >>>>>>>>>>>> Trying bulk load using Hfiles in Spark as below example: >>>>>>>>>>>> >>>>>>>>>>>> import org.apache.spark._ >>>>>>>>>>>> import org.apache.spark.rdd.NewHadoopRDD >>>>>>>>>>>> import org.apache.hadoop.hbase.{HBaseConfiguration, >>>>>>>>>>>> HTableDescriptor} >>>>>>>>>>>> import org.apache.hadoop.hbase.client.HBaseAdmin >>>>>>>>>>>> import org.apache.hadoop.hbase.mapreduce.TableInputFormat >>>>>>>>>>>> import org.apache.hadoop.fs.Path; >>>>>>>>>>>> import org.apache.hadoop.hbase.HColumnDescriptor >>>>>>>>>>>> import org.apache.hadoop.hbase.util.Bytes >>>>>>>>>>>> import org.apache.hadoop.hbase.client.Put; >>>>>>>>>>>> import org.apache.hadoop.hbase.client.HTable; >>>>>>>>>>>> import org.apache.hadoop.hbase.mapred.TableOutputFormat >>>>>>>>>>>> import org.apache.hadoop.mapred.JobConf >>>>>>>>>>>> import org.apache.hadoop.hbase.io.ImmutableBytesWritable >>>>>>>>>>>> import org.apache.hadoop.mapreduce.Jo >>>>>>>>>>>> <http://org.apache.hadoop.mapreduce.jo/>b >>>>>>>>>>>> import org.apache.hadoop.mapreduce.lib.input.FileInputFormat >>>>>>>>>>>> import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat >>>>>>>>>>>> import org.apache.hadoop.hbase.KeyValue >>>>>>>>>>>> import org.apache.hadoop.hbase.mapreduce.HFileOutputFormat >>>>>>>>>>>> import org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles >>>>>>>>>>>> >>>>>>>>>>>> So far no issues. >>>>>>>>>>>> >>>>>>>>>>>> Then I do >>>>>>>>>>>> >>>>>>>>>>>> val conf = HBaseConfiguration.create() >>>>>>>>>>>> conf: org.apache.hadoop.conf.Configuration = Configuration: >>>>>>>>>>>> core-default.xml, core-site.xml, mapred-default.xml, >>>>>>>>>>>> mapred-site.xml, >>>>>>>>>>>> yarn-default.xml, yarn-site.xml, hbase-default.xml, hbase-site.xml >>>>>>>>>>>> val tableName = "testTable" >>>>>>>>>>>> tableName: String = testTable >>>>>>>>>>>> >>>>>>>>>>>> ... > > >
