I'm afraid I use the HDP distribution so I haven't yet had to compile anything. (Incidentally, this isn't a recommendation of HDP over anything else).
On Wed, Dec 30, 2015 at 3:33 PM, Mich Talebzadeh <m...@peridale.co.uk> wrote: > Thanks Marcin > > > > Trying to build TEZ 0.7 in > > > > /usr/lib/apache-tez-0.7.0-src > > > > using > > > > mvn -X clean package -DskipTests=true -Dmaven.javadoc.skip=true > > > > with mvn version 3.2.5 (as opposed to 3.3) as I read that I can build it > OK with 3.2.5 following the same error ass below > > > > mvn --version > > Apache Maven *3.2.5* (12a6b3acb947671f09b81f49094c53f426d8cea1; > 2014-12-14T17:29:23+00:00) > > Maven home: /usr/local/apache-maven/apache-maven-3.2.5 > > Java version: 1.7.0_25, vendor: Oracle Corporation > > Java home: /usr/java/jdk1.7.0_25/jre > > > > *I get this error* > > > > [INFO] tez-ui ............................................. FAILURE [ > 0.411 s] > > [ > > > > DEBUG] -- end configuration -- > > [INFO] Running 'npm install --color=false' in > /usr/lib/apache-tez-0.7.0-src/tez-ui/src/main/webapp > > [INFO] > /usr/lib/apache-tez-0.7.0-src/tez-ui/src/main/webapp/node/with_new_path.sh: > line 3: 23781 Aborted "$@" > > > > > > [ERROR] Failed to execute goal > com.github.eirslett:frontend-maven-plugin:0.0.16:npm (npm install) on > project tez-ui: Failed to run task: 'npm install --color=false' failed. > (error code 134) -> [Help 1] > > org.apache.maven.lifecycle.LifecycleExecutionException: Failed to execute > goal com.github.eirslett:frontend-maven-plugin:0.0.16:npm (npm install) on > project tez-ui: Failed to run task > > > > > > any ideas as there is little info available in net. > > > > > > Thanks > > > > Mich Talebzadeh > > > > *Sybase ASE 15 Gold Medal Award 2008* > > A Winning Strategy: Running the most Critical Financial Data on ASE 15 > > > http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf > > Author of the books* "A Practitioner’s Guide to Upgrading to Sybase ASE > 15", ISBN 978-0-9563693-0-7*. > > co-author *"Sybase Transact SQL Guidelines Best Practices", ISBN > 978-0-9759693-0-4* > > *Publications due shortly:* > > *Complex Event Processing in Heterogeneous Environments*, ISBN: > 978-0-9563693-3-8 > > *Oracle and Sybase, Concepts and Contrasts*, ISBN: 978-0-9563693-1-4, volume > one out shortly > > > > http://talebzadehmich.wordpress.com > > > > NOTE: The information in this email is proprietary and confidential. This > message is for the designated recipient only, if you are not the intended > recipient, you should destroy it immediately. Any information in this > message shall not be understood as given or endorsed by Peridale Technology > Ltd, its subsidiaries or their employees, unless expressly so stated. It is > the responsibility of the recipient to ensure that this email is virus > free, therefore neither Peridale Ltd, its subsidiaries nor their employees > accept any responsibility. > > > > *From:* Marcin Tustin [mailto:mtus...@handybook.com] > *Sent:* 30 December 2015 19:27 > > *To:* user@hive.apache.org > *Subject:* Re: Running the same query on 1 billion rows fact table in > Hive on Spark compared to Sybase IQ columnar database > > > > I'm using TEZ 0.7.0.2.3 with hive 1.2.1.2.3. I can confirm that TEZ is > much faster than MR in pretty much all cases. Also, with hive, you'll make > sure you've performed optimizations like aligning ORC stripe sizes with > HDFS block sizes, and concatenated your tables (not so much an optimization > as a must for avoiding the small files problem). > > > > On Wed, Dec 30, 2015 at 2:19 PM, Mich Talebzadeh <m...@peridale.co.uk> > wrote: > > Thanks again Jorn. > > > > > > Both Hive and Sybase IQ are running on the same host. Yes for Sybase IQ I > have compression enabled. The FACT table in IQ (sales) has LF (read bitmap) > indexes on the time_id column. For the dimension table (times) I have > time_id defined as primary key. Also Sybase IQ creates FP (fast projection) > indexes on every column by default. > > > > Anyway I am trying to download and build TEZ. Do we know which version of > TEZ works with Hive 1.2.1 please? 0.8 seems to be in alpha > > > > Thanks > > > > Mich Talebzadeh > > > > *Sybase ASE 15 Gold Medal Award 2008* > > A Winning Strategy: Running the most Critical Financial Data on ASE 15 > > > http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf > > Author of the books* "A Practitioner’s Guide to Upgrading to Sybase ASE > 15", ISBN 978-0-9563693-0-7*. > > co-author *"Sybase Transact SQL Guidelines Best Practices", ISBN > 978-0-9759693-0-4* > > *Publications due shortly:* > > *Complex Event Processing in Heterogeneous Environments*, ISBN: > 978-0-9563693-3-8 > > *Oracle and Sybase, Concepts and Contrasts*, ISBN: 978-0-9563693-1-4, volume > one out shortly > > > > http://talebzadehmich.wordpress.com > > > > NOTE: The information in this email is proprietary and confidential. This > message is for the designated recipient only, if you are not the intended > recipient, you should destroy it immediately. Any information in this > message shall not be understood as given or endorsed by Peridale Technology > Ltd, its subsidiaries or their employees, unless expressly so stated. It is > the responsibility of the recipient to ensure that this email is virus > free, therefore neither Peridale Ltd, its subsidiaries nor their employees > accept any responsibility. > > > > *From:* Jörn Franke [mailto:jornfra...@gmail.com] > *Sent:* 30 December 2015 16:29 > > > *To:* user@hive.apache.org > *Subject:* Re: Running the same query on 1 billion rows fact table in > Hive on Spark compared to Sybase IQ columnar database > > > > > Hmm i think the execution Engine TEZ has (currently) the most > optimizations on Hive. What about your hardware - is it the same? Do you > have also compression on Sybase? > > Alternatively you need to wait for Hive for interactive analytics (tez 0.8 > + llap). > > > On 30 Dec 2015, at 13:47, Mich Talebzadeh <m...@peridale.co.uk> wrote: > > Hi Jorn, > > > > Thanks for your reply. My Hive version is 1.2.1 on Spark 1.3.1. I have not > tried it on TEZ. I tried the query on MR engine and it did nor fair better. > I also ran it without SDDDEV function and found out that the function did > not slow it down. > > > > I tried a simple query as follows builr in sales FACT table 1e9 rows and > dimension table times (1826 rows) > > > > -- > > -- Get the total amount sold for each calendar month > > -- > > *SELECT t.calendar_month_desc, SUM(s.amount_sold)* > > *FROM sales s, times t WHERE s.time_id = t.time_id* > > *GROUP BY t.calendar_month_desc;* > > > > Now Sybase IQ comes back in around 30 seconds. > > > > Started query at Dec 30 2015 08:14:33:399AM > > (48 rows affected) > > Finished query at Dec 30 2015 08:15:04:640AM > > > > Whereas Hive with the following setting and running the same query > > > > set > hive.input.format=org.apache.hadoop.hive.ql.io.BucketizedHiveInputFormat; > > set hive.optimize.bucketmapjoin=true; > > set hive.optimize.bucketmapjoin.sortedmerge=true; > > > > Comes back in > > > > 48 rows selected (1514.687 seconds) > > > > I don’t know what else can be done. Obviously this is all schema on read > so I am not sure I can change bucketing on FACT table based on one query > alone! > > > > > > > > +--------------------------------------------------------------------+--+ > > | createtab_stmt | > > +--------------------------------------------------------------------+--+ > > | CREATE TABLE `times`( | > > | `time_id` timestamp, | > > | `day_name` varchar(9), | > > | `day_number_in_week` int, | > > | `day_number_in_month` int, | > > | `calendar_week_number` int, | > > | `fiscal_week_number` int, | > > | `week_ending_day` timestamp, | > > | `week_ending_day_id` bigint, | > > | `calendar_month_number` int, | > > | `fiscal_month_number` int, | > > | `calendar_month_desc` varchar(8), | > > ---------- > > | `days_in_fis_year` bigint, | > > | `end_of_cal_year` timestamp, | > > | `end_of_fis_year` timestamp) | > > | CLUSTERED BY ( | > > | time_id) | > > | INTO 256 BUCKETS | > > | ROW FORMAT SERDE | > > | 'org.apache.hadoop.hive.ql.io.orc.OrcSerde' | > > | STORED AS INPUTFORMAT | > > | 'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat' | > > | OUTPUTFORMAT | > > | 'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat' | > > | LOCATION | > > | 'hdfs://rhes564:9000/user/hive/warehouse/oraclehadoop.db/times' | > > | TBLPROPERTIES ( | > > | 'COLUMN_STATS_ACCURATE'='true', | > > | 'numFiles'='1', | > > | 'numRows'='1826', | > > | 'orc.bloom.filter.columns'='TIME_ID', | > > | 'orc.bloom.filter.fpp'='0.05', | > > | 'orc.compress'='SNAPPY', | > > | 'orc.create.index'='true', | > > | 'orc.row.index.stride'='10000', | > > | 'orc.stripe.size'='268435456', | > > | 'rawDataSize'='0', | > > | 'totalSize'='11155', | > > | 'transient_lastDdlTime'='1451429900') | > > > > ; > > > > > > http://talebzadehmich.wordpress.com > > > > NOTE: The information in this email is proprietary and confidential. This > message is for the designated recipient only, if you are not the intended > recipient, you should destroy it immediately. Any information in this > message shall not be understood as given or endorsed by Peridale Technology > Ltd, its subsidiaries or their employees, unless expressly so stated. It is > the responsibility of the recipient to ensure that this email is virus > free, therefore neither Peridale Ltd, its subsidiaries nor their employees > accept any responsibility. > > > > *From:* Jörn Franke [mailto:jornfra...@gmail.com <jornfra...@gmail.com>] > *Sent:* 30 December 2015 08:28 > *To:* user@hive.apache.org > *Subject:* Re: Running the same query on 1 billion rows fact table in > Hive on Spark compared to Sybase IQ columnar database > > > > Have you tried it with Hive ob TEZ? It contains (currently) more > optimizations than Hive on Spark. > > I assume you use the latest Hive version. > > Additionally you may want to think about calculating statistics (depending > on your configuration you need to trigger it) - I am not sure if Spark can > use them. > > I am not sure if bloom filters on the columns you mention make sense. You > may also want to increase stride size (depending on your data). > > Currently you bucket by a lot of fields, which may not make sense. You > also may want to sort the data by customer Id in the table. > > You also seem to have a lot of reducers, which you may want to decrease. > > > > Have you tried without "having stddev_samp" ? Is the query exactly the > same as in Sybase? > > > On 29 Dec 2015, at 11:53, Mich Talebzadeh <m...@peridale.co.uk> wrote: > > Hi, > > > > I have a fact table in Hive imported from Sybase IQ via SQOOP with 1 > billion rows as follows: > > > > show create table sales; > > > +-------------------------------------------------------------------------------+--+ > > | > createtab_stmt | > > > +-------------------------------------------------------------------------------+--+ > > | CREATE TABLE > `sales`( | > > | `prod_id` > bigint, | > > | `cust_id` > bigint, | > > | `time_id` > timestamp, | > > | `channel_id` > bigint, | > > | `promo_id` > bigint, | > > | `quantity_sold` > decimal(10,0), | > > | `amount_sold` > decimal(10,0)) | > > | CLUSTERED BY ( > | > > | > prod_id, > | > > | > cust_id, > | > > | time_id, > | > > | > channel_id, > | > > | > promo_id) > | > > | INTO 256 BUCKETS > | > > | ROW FORMAT > SERDE | > > | > 'org.apache.hadoop.hive.ql.io.orc.OrcSerde' > | > > | STORED AS INPUTFORMAT > | > > | > 'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat' > | > > | > OUTPUTFORMAT > | > > | 'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat' > | > > | > LOCATION > | > > | > 'hdfs://rhes564:9000/user/hive/warehouse/oraclehadoop.db/sales' > | > > | TBLPROPERTIES > ( | > > | > 'COLUMN_STATS_ACCURATE'='true', > | > > | > 'last_modified_by'='hduser', > | > > | > 'last_modified_time'='1451305626', > | > > | > 'numFiles'='11', > | > > | > 'numRows'='1000000000', > | > > | > 'orc.bloom.filter.columns'='PROD_ID,CUST_ID,TIME_ID,CHANNEL_ID,PROMO_ID', > | > > | > 'orc.bloom.filter.fpp'='0.05', > | > > | > 'orc.compress'='SNAPPY', > | > > | > 'orc.create.index'='true', > | > > | > 'orc.row.index.stride'='10000', > | > > | > 'orc.stripe.size'='268435456', > | > > | > 'rawDataSize'='296000000000', > | > > | 'totalSize'='2678882153', > | > > | > 'transient_lastDdlTime'='1451305626') > | > > > +-------------------------------------------------------------------------------+--+ > > > > I use the following query to run against sales table only against Hive > > > > SELECT > > rs.Customer_ID > > , rs.Number_of_orders > > , rs.Total_customer_amount > > , rs.Average_order > > , rs.Standard_deviation > > FROM > > ( > > SELECT cust_id AS Customer_ID, > > COUNT(amount_sold) AS Number_of_orders, > > SUM(amount_sold) AS Total_customer_amount, > > AVG(amount_sold) AS Average_order, > > stddev_samp(amount_sold) AS Standard_deviation > > FROM sales > > GROUP BY cust_id > > HAVING SUM(amount_sold) > 94000 > > AND AVG(amount_sold) < stddev_samp(amount_sold) > > ) rs > > ORDER BY > > -- Total_customer_amount DESC > > 3 DESC > > > > Hive comes back in 17 minutes with 5,948 rows > > > > bl -f sales.hql > sales.log > > Connecting to jdbc:hive2://rhes564:10010/default > > Connected to: Apache Hive (version 1.2.1) > > Driver: Hive JDBC (version 1.2.1) > > Transaction isolation: TRANSACTION_REPEATABLE_READ > > Running init script /home/hduser/dba/bin/hive_on_spark_init.hql > > No rows affected (0.097 seconds) > > No rows affected (0.001 seconds) > > No rows affected (0.001 seconds) > > No rows affected (0.038 seconds) > > INFO : Warning: Using constant number 3 in order by. If you try to use > position alias when hive.groupby.orderby.position.alias is false, the > position alias will be ignored. > > INFO : > > Query Hive on Spark job[0] stages: > > INFO : 0 > > INFO : 1 > > INFO : 2 > > INFO : > > Status: Running (Hive on Spark job[0]) > > INFO : Job Progress Format > > CurrentTime StageId_StageAttemptId: > SucceededTasksCount(+RunningTasksCount-FailedTasksCount)/TotalTasksCount > [StageCost] > > INFO : 2015-12-29 09:33:25,815 Stage-0_0: 0/11 Stage-1_0: 0/1009 > Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:28,829 Stage-0_0: 0/11 Stage-1_0: 0/1009 > Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:31,857 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:34,875 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:37,903 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:40,918 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:43,939 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:46,958 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:49,971 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:52,991 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:33:56,007 Stage-0_0: 0(+2)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > > > INFO : 2015-12-29 09:50:03,578 Stage-0_0: 10(+1)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:06,590 Stage-0_0: 10(+1)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:09,602 Stage-0_0: 10(+1)/11 Stage-1_0: > 0/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:10,606 Stage-0_0: 11/11 Finished Stage-1_0: > 0(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:11,610 Stage-0_0: 11/11 Finished Stage-1_0: > 6(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:12,618 Stage-0_0: 11/11 Finished Stage-1_0: > 30(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:13,622 Stage-0_0: 11/11 Finished Stage-1_0: > 59(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:14,626 Stage-0_0: 11/11 Finished Stage-1_0: > 90(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:15,631 Stage-0_0: 11/11 Finished Stage-1_0: > 124(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:16,654 Stage-0_0: 11/11 Finished Stage-1_0: > 160(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:17,659 Stage-0_0: 11/11 Finished Stage-1_0: > 193(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:18,663 Stage-0_0: 11/11 Finished Stage-1_0: > 228(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:19,667 Stage-0_0: 11/11 Finished Stage-1_0: > 262(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:20,672 Stage-0_0: 11/11 Finished Stage-1_0: > 298(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:21,679 Stage-0_0: 11/11 Finished Stage-1_0: > 338(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:22,687 Stage-0_0: 11/11 Finished Stage-1_0: > 376(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:23,691 Stage-0_0: 11/11 Finished Stage-1_0: > 417(+3)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:24,696 Stage-0_0: 11/11 Finished Stage-1_0: > 460(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:25,699 Stage-0_0: 11/11 Finished Stage-1_0: > 502(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:26,707 Stage-0_0: 11/11 Finished Stage-1_0: > 542(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:27,712 Stage-0_0: 11/11 Finished Stage-1_0: > 584(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:28,719 Stage-0_0: 11/11 Finished Stage-1_0: > 624(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:29,730 Stage-0_0: 11/11 Finished Stage-1_0: > 667(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:30,736 Stage-0_0: 11/11 Finished Stage-1_0: > 709(+3)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:31,740 Stage-0_0: 11/11 Finished Stage-1_0: > 754(+3)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:32,743 Stage-0_0: 11/11 Finished Stage-1_0: > 797(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:33,747 Stage-0_0: 11/11 Finished Stage-1_0: > 844(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:34,754 Stage-0_0: 11/11 Finished Stage-1_0: > 888(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:35,759 Stage-0_0: 11/11 Finished Stage-1_0: > 934(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:36,764 Stage-0_0: 11/11 Finished Stage-1_0: > 981(+2)/1009 Stage-2_0: 0/1 > > INFO : 2015-12-29 09:50:37,768 Stage-0_0: 11/11 Finished Stage-1_0: > 1009/1009 Finished Stage-2_0: 0(+1)/1 > > INFO : 2015-12-29 09:50:38,771 Stage-0_0: 11/11 Finished Stage-1_0: > 1009/1009 Finished Stage-2_0: 1/1 Finished > > INFO : Status: Finished successfully in 1036.00 seconds > > *5,948 rows selected (1074.817 seconds)* > > > > So it returns 5948 rows in 17 minutes. In contrast IQ returns 5947 rows in > 23 seconds > > > > Sybase IQ is a columnar database so each column is created as a fast > projection index by default. In addition I have created LF (bitmap) indexes > on dimension columns (PROD_ID, CUST_ID, TIME_ID, CHANNEL_ID, PROMO_ID). Now > the query only touches CUST_ID. > > > > My suspicion is that it is the Standard Deviation function stddev_samp() that > could be the bottleneck? > > > > Thanks > > > > Mich Talebzadeh > > > > *Sybase ASE 15 Gold Medal Award 2008* > > A Winning Strategy: Running the most Critical Financial Data on ASE 15 > > > http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf > > Author of the books* "A Practitioner’s Guide to Upgrading to Sybase ASE > 15", ISBN 978-0-9563693-0-7*. > > co-author *"Sybase Transact SQL Guidelines Best Practices", ISBN > 978-0-9759693-0-4* > > *Publications due shortly:* > > *Complex Event Processing in Heterogeneous Environments*, ISBN: > 978-0-9563693-3-8 > > *Oracle and Sybase, Concepts and Contrasts*, ISBN: 978-0-9563693-1-4, volume > one out shortly > > > > http://talebzadehmich.wordpress.com > > > > NOTE: The information in this email is proprietary and confidential. This > message is for the designated recipient only, if you are not the intended > recipient, you should destroy it immediately. Any information in this > message shall not be understood as given or endorsed by Peridale Technology > Ltd, its subsidiaries or their employees, unless expressly so stated. It is > the responsibility of the recipient to ensure that this email is virus > free, therefore neither Peridale Ltd, its subsidiaries nor their employees > accept any responsibility. > > > > > > > > Want to work at Handy? Check out our culture deck and open roles > <http://www.handy.com/careers> > > Latest news <http://www.handy.com/press> at Handy > > Handy just raised $50m > <http://venturebeat.com/2015/11/02/on-demand-home-service-handy-raises-50m-in-round-led-by-fidelity/> > led > by Fidelity > > > > [image: Image removed by sender.] > -- Want to work at Handy? Check out our culture deck and open roles <http://www.handy.com/careers> Latest news <http://www.handy.com/press> at Handy Handy just raised $50m <http://venturebeat.com/2015/11/02/on-demand-home-service-handy-raises-50m-in-round-led-by-fidelity/> led by Fidelity
