Saturday, May 18, 2013

Query HBase tables with Impala


As described in other blog posts, Impala uses Hive Metastore Service to query the underlaying data. In this post I use the Hive-HBase handler to connect Hive and HBase and query the data later with Impala. In the past I've written a tutorial (http://mapredit.blogspot.de/2012/12/using-hives-hbase-handler.html) how to connect HBase and Hive, please follow the instructions there.

This approach offers Data Scientists a wide field of work with data stored in HDFS and / or HBase. You will get the possibility to run queries against your stored data independently which technology and database do you use, simply by querying the different data sources in a fast and easy way.

I use the official available census data gathered in 2000 by the US government. The goal is to push this data as CSV into HBase and query this table per Impala. I've made a demonstration script which is available in my git repository.

Demonstration scenario

The dataset looks pretty simple:

cat DEC_00_SF3_P077_with_ann_noheader.csv

8600000US00601,00601,006015-DigitZCTA,0063-DigitZCTA,11102
8600000US00602,00602,006025-DigitZCTA,0063-DigitZCTA,12869
8600000US00603,00603,006035-DigitZCTA,0063-DigitZCTA,12423
8600000US00604,00604,006045-DigitZCTA,0063-DigitZCTA,33548
8600000US00606,00606,006065-DigitZCTA,0063-DigitZCTA,10603

Create the HBase table:

create 'zipcode_hive', 'id', 'zip', 'desc', 'income'

and create an external table in Hive which looks as follows:

CREATE EXTERNAL TABLE ZIPCODE_HBASE (key STRING,zip STRING,desc1 STRING,desc2 STRING,income STRING) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler' WITH SERDEPROPERTIES ("hbase.columns.mapping" = ":key,zip:zip,desc:desc1,desc:desc2,income:income") TBLPROPERTIES("hbase.table.name" = "zipcode_hive");

Here we map the Hive tables per HBaseStorageHandler to the HBase scheme we've used in the step above.

After these steps are successfully finished, we need to copy the CSV data into HBase. I chose Pig for this task but you can use a translate table in Hive, too.

Here's my Pig script:

cat PopulateData.pig


copyFromLocal DEC_00_SF3_P077_with_ann_noheader.csv ziptest.csv
A = LOAD 'ziptest.csv' USING PigStorage(',') as (id:chararray, zip:chararray, desc1:chararray, desc2:chararray, income:chararray); STORE A INTO 'hbase://zipcode_hive' USING org.apache.pig.backend.hadoop.hbase.HBaseStorage('zip:zip,desc:desc1,desc:desc2,income:income');

The job takes a few seconds and the data is available per HBase:

scan 'zipcode_hive', LIMIT => 2


ROW                                    COLUMN+CELL                                                                                                    
 8600000US00601                        column=desc:desc1, timestamp=1368880594523, value=006015-DigitZCTA                                             
 8600000US00601                        column=desc:desc2, timestamp=1368880594523, value=0063-DigitZCTA                                               
 8600000US00601                        column=income:income, timestamp=1368880594523, value=11102                                                     
 8600000US00601                        column=zip:zip, timestamp=1368880594523, value=00601                                                           
 8600000US00602                        column=desc:desc1, timestamp=1368880594523, value=006025-DigitZCTA                                             
 8600000US00602                        column=desc:desc2, timestamp=1368880594523, value=0063-DigitZCTA                                               
 8600000US00602                        column=income:income, timestamp=1368880594523, value=12869                                                     
 8600000US00602                        column=zip:zip, timestamp=1368880594523, value=00602 

Now we do the same with Impala:

select * from zipcode_hbase limit 4


Using service name 'impala' for kerberos
Connected to hadoop1:21000
Server version: impalad version 1.0 RELEASE (build d1bf0d1dac339af3692ffa17a5e3fdae0aed751f)
Query: select *
from ZIPCODE_HBASE limit 4
Query finished, fetching results ...
+----------------+------------------+----------------+--------+-------+
| key            | desc1            | desc2          | income | zip   |
+----------------+------------------+----------------+--------+-------+
| 8600000US00601 | 006015-DigitZCTA | 0063-DigitZCTA | 11102  | 00601 |
| 8600000US00602 | 006025-DigitZCTA | 0063-DigitZCTA | 12869  | 00602 |
| 8600000US00603 | 006035-DigitZCTA | 0063-DigitZCTA | 12423  | 00603 |
| 8600000US00604 | 006045-DigitZCTA | 0063-DigitZCTA | 33548  | 00604 |
+----------------+------------------+----------------+--------+-------+
Returned 4 row(s) in 0.42s

Another query to get the incomes between 1,000 and 5,000 US$, sorted by income:

select * from zipcode_hbase where income between '1000' and '5000' order by income DESC limit 20;


+----------------+------------------+----------------+--------+-------+
| key            | desc1            | desc2          | income | zip   |
+----------------+------------------+----------------+--------+-------+
| 8600000US64138 | 641385-DigitZCTA | 6413-DigitZCTA | 49995  | 64138 |
| 8600000US12477 | 124775-DigitZCTA | 1243-DigitZCTA | 49993  | 12477 |
| 8600000US33025 | 330255-DigitZCTA | 3303-DigitZCTA | 49991  | 33025 |
| 8600000US44119 | 441195-DigitZCTA | 4413-DigitZCTA | 49988  | 44119 |
| 8600000US34997 | 349975-DigitZCTA | 3493-DigitZCTA | 49982  | 34997 |
| 8600000US70665 | 706655-DigitZCTA | 7063-DigitZCTA | 49981  | 70665 |
| 8600000US28625 | 286255-DigitZCTA | 2863-DigitZCTA | 49981  | 28625 |
| 8600000US76134 | 761345-DigitZCTA | 7613-DigitZCTA | 49979  | 76134 |
| 8600000US44618 | 446185-DigitZCTA | 4463-DigitZCTA | 49978  | 44618 |
| 8600000US65714 | 657145-DigitZCTA | 6573-DigitZCTA | 49978  | 65714 |
| 8600000US77338 | 773385-DigitZCTA | 7733-DigitZCTA | 49976  | 77338 |
| 8600000US14622 | 146225-DigitZCTA | 1463-DigitZCTA | 49972  | 14622 |
| 8600000US84339 | 843395-DigitZCTA | 8433-DigitZCTA | 49972  | 84339 |
| 8600000US85020 | 850205-DigitZCTA | 8503-DigitZCTA | 49967  | 85020 |
| 8600000US64061 | 640615-DigitZCTA | 6403-DigitZCTA | 49964  | 64061 |
| 8600000US97361 | 973615-DigitZCTA | 9733-DigitZCTA | 49961  | 97361 |
| 8600000US30008 | 300085-DigitZCTA | 3003-DigitZCTA | 49960  | 30008 |
| 8600000US48634 | 486345-DigitZCTA | 4863-DigitZCTA | 49958  | 48634 |
| 8600000US47923 | 479235-DigitZCTA | 4793-DigitZCTA | 49946  | 47923 |
| 8600000US46958 | 469585-DigitZCTA | 4693-DigitZCTA | 49946  | 46958 |
+----------------+------------------+----------------+--------+-------+
Returned 20 row(s) in 1.08s