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05-25-2022
11:28 PM
@TonyQiu Sorry been away for a while. Creating a table in a kerberized cluster should be possible as hbase. I just tried it out see the flow below.. I didn't need to specifically kinit as the user hbase had a valid Kerberos ticket Switch to hbase user [root@malindi keytabs]# su - hbase
Last login: Wed May 25 21:51:56 CEST 2022 Check if kerberos ticket is valid [hbase@malindi ~]$ klist
Ticket cache: FILE:/tmp/krb5cc_1016
Default principal: hbase-jair@KENYA.KE
Valid starting Expires Service principal
05/25/2022 21:51:57 05/26/2022 21:51:57 krbtgt/KENYA.KE@KENYA.KE Connect to hbase shell as hbase [hbase@malindi ~]$ hbase-shell List existing tables hbase(main):006:0> list
TABLE
ATLAS_ENTITY_AUDIT_EVENTS
atlas_titan
2 row(s) in 0.6660 seconds
=> ["ATLAS_ENTITY_AUDIT_EVENTS", "atlas_titan"] Create table emp hbase(main):007:0> create 'emp', 'personal data', 'professional data'
0 row(s) in 4.9500 seconds
=> Hbase::Table - emp List tables validate emp was created hbase(main):009:0> list
TABLE
ATLAS_ENTITY_AUDIT_EVENTS
atlas_titan
emp
3 row(s) in 0.0130 seconds
=> ["ATLAS_ENTITY_AUDIT_EVENTS", "atlas_titan", "emp"] Describe table emp hbase(main):010:0> describe 'emp'
Table emp is ENABLED
emp
COLUMN FAMILIES DESCRIPTION
{NAME => 'personal data', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERSIONS
=> '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'}
{NAME => 'professional data', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERS
IONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'}
2 row(s) in 0.8770 seconds Update table hbase(main):011:0> alter 'emp', {NAME => 'metrics', BLOCKSIZE => '16384', COMPRESSION => 'SNAPPY'}
Updating all regions with the new schema...
0/1 regions updated.
1/1 regions updated.
Done.
0 row(s) in 4.9660 seconds Can you share your snippet?
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