Once again, we connect to the edge using SSH:
$ ssh istepanian@hadoop-edge01.efrei.online
Welcome to EFREI Hadoop Cluster
Password:
Last login: Mon Nov 16 16:11:01 2020 from XX-XXX-XX-XX.XXX.XXXXXXX.XXX
-sh-4.2$It isn't necessary to manually initialize a new Kerberos ticket, as it is automatically created.
-sh-4.2$ klist
Ticket cache: FILE:/tmp/krb5cc_20170518
Default principal: istepanian@EFREI.ONLINE
Valid starting Expires Service principal
17/11/2020 15:27:17 18/11/2020 15:27:17 krbtgt/EFREI.ONLINE@EFREI.ONLINE
renew until 24/11/2020 15:27:17We can launch the HBase Client (Shell) by using the hbase shell command.
-sh-4.2$ hbase shell
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/hdp/3.1.5.0-152/hadoop/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/3.1.5.0-152/hbase/lib/client-facing-thirdparty/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
HBase Shell
Use "help" to get list of supported commands.
Use "exit" to quit this interactive shell.
For Reference, please visit: http://hbase.apache.org/2.0/book.html#shell
Version 2.1.6.3.1.5.0-152, rUnknown, Thu Dec 12 20:16:57 UTC 2019
Took 0.0039 seconds
hbase(main):001:0> status
1 active master, 1 backup masters, 3 servers, 0 dead, 13.3333 average load
Took 0.4078 seconds
hbase(main):002:0> version
2.1.6.3.1.5.0-152, rUnknown, Thu Dec 12 20:16:57 UTC 2019
Took 0.0007 seconds
hbase(main):003:0> whoami
istepanian@EFREI.ONLINE (auth:KERBEROS)
groups: istepanian, hadoop-users
Took 0.0297 seconds
hbase(main):004:0> list
TABLE
ATLAS_ENTITY_AUDIT_EVENTS
agoncalves:library
agoubeau:library
atlas_titan
ccarayon:library
cloupec:library
cmarcou:library
cspatz:library
dsonethavy:library
enitschke:library
fshonggeu:library
gjaouen:library
gshanmuganathapillai:library
idelaronciere:library
imuntz:library
jly:library
jtang:library
jtran:library
kkouadio:library
lbenyamin:library
lboumriche:library
ldelthil:library
lvaio:library
mbartier:library
mbury:library
mebrahim:library
pchen:library
pdorffer:library
psalvaudon:library
qcourtois:library
skeutcha:library
tdura:library
32 row(s)
Took 0.0391 seconds
=> ["ATLAS_ENTITY_AUDIT_EVENTS", "agoncalves:library", "agoubeau:library", "atlas_titan", "ccarayon:library", "cloupec:library", "cmarcou:library", "cspatz:library", "dsonethavy:library", "enitschke:library", "fshonggeu:library", "gjaouen:library", "gshanmuganathapillai:library", "idelaronciere:library", "imuntz:library", "jly:library", "jtang:library", "jtran:library", "kkouadio:library", "lbenyamin:library", "lboumriche:library", "ldelthil:library", "lvaio:library", "mbartier:library", "mbury:library", "mebrahim:library", "pchen:library", "pdorffer:library", "psalvaudon:library", "qcourtois:library", "skeutcha:library", "tdura:library"]
hbase(main):005:0> exit
-sh-4.2$list allows us to see all the tables created in the system; we can see the namespaces (and tables) created by the other users.
We can see all available HBase commands using the help command.
hbase(main):001:0> help
HBase Shell, version 2.1.6.3.1.5.0-152, rUnknown, Thu Dec 12 20:16:57 UTC 2019
Type 'help "COMMAND"', (e.g. 'help "get"' -- the quotes are necessary) for help on a specific command.
Commands are grouped. Type 'help "COMMAND_GROUP"', (e.g. 'help "general"') for help on a command group.
COMMAND GROUPS:
Group name: general
Commands: processlist, status, table_help, version, whoami
Group name: ddl
Commands: alter, alter_async, alter_status, clone_table_schema, create, describe, disable, disable_all, drop, drop_all, enable, enable_all, exists, get_table, is_disabled, is_enabled, list, list_regions, locate_region, show_filters
Group name: namespace
Commands: alter_namespace, create_namespace, describe_namespace, drop_namespace, list_namespace, list_namespace_tables
Group name: dml
Commands: append, count, delete, deleteall, get, get_counter, get_splits, incr, put, scan, truncate, truncate_preserve
Group name: tools
Commands: assign, balance_switch, balancer, balancer_enabled, catalogjanitor_enabled, catalogjanitor_run, catalogjanitor_switch, cleaner_chore_enabled, cleaner_chore_run, cleaner_chore_switch, clear_block_cache, clear_compaction_queues, clear_deadservers, close_region, compact, compact_rs, compaction_state, flush, hbck_chore_run, is_in_maintenance_mode, list_deadservers, major_compact, merge_region, move, normalize, normalizer_enabled, normalizer_switch, split, splitormerge_enabled, splitormerge_switch, stop_master, stop_regionserver, trace, unassign, wal_roll, zk_dump
Group name: replication
Commands: add_peer, append_peer_exclude_namespaces, append_peer_exclude_tableCFs, append_peer_namespaces, append_peer_tableCFs, disable_peer, disable_table_replication, enable_peer, enable_table_replication, get_peer_config, list_peer_configs, list_peers, list_replicated_tables, remove_peer, remove_peer_exclude_namespaces, remove_peer_exclude_tableCFs, remove_peer_namespaces, remove_peer_tableCFs, set_peer_bandwidth, set_peer_exclude_namespaces, set_peer_exclude_tableCFs, set_peer_namespaces, set_peer_replicate_all, set_peer_serial, set_peer_tableCFs, show_peer_tableCFs, update_peer_config
Group name: snapshots
Commands: clone_snapshot, delete_all_snapshot, delete_snapshot, delete_table_snapshots, list_snapshots, list_table_snapshots, restore_snapshot, snapshot
Group name: configuration
Commands: update_all_config, update_config
Group name: quotas
Commands: list_quota_snapshots, list_quota_table_sizes, list_quotas, list_snapshot_sizes, set_quota
Group name: security
Commands: grant, list_security_capabilities, revoke, user_permission
Group name: procedures
Commands: list_locks, list_procedures
Group name: visibility labels
Commands: add_labels, clear_auths, get_auths, list_labels, set_auths, set_visibility
Group name: rsgroup
Commands: add_rsgroup, balance_rsgroup, get_rsgroup, get_server_rsgroup, get_table_rsgroup, list_rsgroups, move_namespaces_rsgroup, move_servers_namespaces_rsgroup, move_servers_rsgroup, move_servers_tables_rsgroup, move_tables_rsgroup, remove_rsgroup, remove_servers_rsgroup
SHELL USAGE:
Quote all names in HBase Shell such as table and column names. Commas delimit
command parameters. Type <RETURN> after entering a command to run it.
Dictionaries of configuration used in the creation and alteration of tables are
Ruby Hashes. They look like this:
{'key1' => 'value1', 'key2' => 'value2', ...}
and are opened and closed with curley-braces. Key/values are delimited by the
'=>' character combination. Usually keys are predefined constants such as
NAME, VERSIONS, COMPRESSION, etc. Constants do not need to be quoted. Type
'Object.constants' to see a (messy) list of all constants in the environment.
If you are using binary keys or values and need to enter them in the shell, use
double-quote'd hexadecimal representation. For example:
hbase> get 't1', "key\x03\x3f\xcd"
hbase> get 't1', "key\003\023\011"
hbase> put 't1', "test\xef\xff", 'f1:', "\x01\x33\x40"
The HBase shell is the (J)Ruby IRB with the above HBase-specific commands added.
For more on the HBase Shell, see http://hbase.apache.org/book.htmlAll the namespace commands are in the Group name: namespace section. The right command to create a namespace is create_namespace "<name>"
hbase(main):002:0> create_namespace "istepanian"
Took 0.5880 seconds
hbase(main):003:0> list_namespace
NAMESPACE
agoncalves
agoubeau
aledeuf
apauly
apignerol
avignaud
ccarayon
cloupec
cmarcou
comnes
cspatz
default
dsonethavy
ebertin
enitschke
fshonggeu
gjaouen
gshanmuganathapillai
hbase
idelaronciere
imuntz
istepanian
jly
jtang
jtran
kkouadio
lbenyamin
lboumriche
ldelthil
lgailhac
lvaio
mbartier
mbury
mebrahim
meccher
mhatoum
nsahnou
oallouache
pchen
pdorffer
psalvaudon
qcourtois
rcailliot
sborongobialibawa
skeutcha
ssedraoui
tdura
ttea
vserena
49 row(s)
Took 0.0434 seconds
hbase(main):004:0>Our namespace has correctly been created.
To easily create the table and precise both the name and the number of versions of the column families, we write the command using Ruby notation.
hbase(main):005:0> create 'istepanian:library', {NAME => 'author', VERSIONS => 2}, {NAME => 'book', VERSIONS => 3}
Created table istepanian:library
Took 0.7625 seconds
=> Hbase::Table - istepanian:library
hbase(main):006:0> describe 'istepanian:library'
Table istepanian:library is ENABLED
istepanian:library
COLUMN FAMILIES DESCRIPTION
{NAME => 'author', VERSIONS => '2', EVICT_BLOCKS_ON_CLOSE => 'false', NEW_VERSION_BEHAVIOR => 'false', KEEP_DELETED_CELLS => 'FALSE', CACHE_DATA_ON
_WRITE => 'false', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', MIN_VERSIONS => '0', REPLICATION_SCOPE => '0', BLOOMFILTER => 'ROW', CACHE_INDE
X_ON_WRITE => 'false', IN_MEMORY => 'false', CACHE_BLOOMS_ON_WRITE => 'false', PREFETCH_BLOCKS_ON_OPEN => 'false', COMPRESSION => 'NONE', BLOCKCACH
E => 'true', BLOCKSIZE => '65536'}
{NAME => 'book', VERSIONS => '3', EVICT_BLOCKS_ON_CLOSE => 'false', NEW_VERSION_BEHAVIOR => 'false', KEEP_DELETED_CELLS => 'FALSE', CACHE_DATA_ON_W
RITE => 'false', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', MIN_VERSIONS => '0', REPLICATION_SCOPE => '0', BLOOMFILTER => 'ROW', CACHE_INDEX_
ON_WRITE => 'false', IN_MEMORY => 'false', CACHE_BLOOMS_ON_WRITE => 'false', PREFETCH_BLOCKS_ON_OPEN => 'false', COMPRESSION => 'NONE', BLOCKCACHE
=> 'true', BLOCKSIZE => '65536'}
2 row(s)
Took 0.1385 seconds
hbase(main):007:0> scan 'istepanian:library'
ROW COLUMN+CELL
0 row(s)
Took 0.1325 seconds
hbase(main):008:0> is_enabled 'istepanian:library'
true
Took 0.0113 seconds
=> true
hbase(main):009:0>The table is enabled by default.
Using put
<row_key> , we can create our new rows 'vhugo' and 'jverne' in our newly created tablelibrary.
hbase(main):003:0> put 'istepanian:library', 'vhugo', 'author:lastname', 'Hugo'
Took 0.0070 seconds
hbase(main):004:0> put 'istepanian:library', 'vhugo', 'book:title', 'La Légende des siècles'
Took 0.0050 seconds
hbase(main):005:0> put 'istepanian:library', 'vhugo', 'book:categ', 'Poèmes'
Took 0.0061 seconds
hbase(main):006:0> put 'istepanian:library', 'vhugo', 'book:year', 1855
Took 0.0047 seconds
hbase(main):007:0> put 'istepanian:library', 'vhugo', 'book:year', 1877
Took 0.0048 seconds
hbase(main):008:0> put 'istepanian:library', 'vhugo', 'book:year', 1883
Took 0.0048 seconds
hbase(main):009:0> put 'istepanian:library', 'jverne', 'author:firstname', 'Jules'
Took 0.0046 seconds
hbase(main):010:0> put 'istepanian:library', 'jverne', 'author:lastname', 'Verne'
Took 0.0045 seconds
hbase(main):011:0> put 'istepanian:library', 'jverne', 'book:publisher', 'Hetzel'
Took 0.0049 seconds
hbase(main):012:0> put 'istepanian:library', 'jverne', 'book:title', 'Face au drapeau'
Took 0.0048 seconds
hbase(main):013:0> put 'istepanian:library', 'jverne', 'book:year', 1896
Took 0.0049 secondsIn the Group name: ddl of the help page, we can see that there is a count command. Using help "count", we can get details about the command usage.
hbase(main):001:0> help "count"
Count the number of rows in a table. Return value is the number of rows.
This operation may take a LONG time (Run '$HADOOP_HOME/bin/hadoop jar
hbase.jar rowcount' to run a counting mapreduce job). Current count is shown
every 1000 rows by default. Count interval may be optionally specified. Scan
caching is enabled on count scans by default. Default cache size is 10 rows.
If your rows are small in size, you may want to increase this
parameter. Examples:
hbase> count 'ns1:t1'
hbase> count 't1'
hbase> count 't1', INTERVAL => 100000
hbase> count 't1', CACHE => 1000
hbase> count 't1', INTERVAL => 10, CACHE => 1000
hbase> count 't1', FILTER => "
(QualifierFilter (>=, 'binary:xyz')) AND (TimestampsFilter ( 123, 456))"
hbase> count 't1', COLUMNS => ['c1', 'c2'], STARTROW => 'abc', STOPROW => 'xyz'
The same commands also can be run on a table reference. Suppose you had a reference
t to table 't1', the corresponding commands would be:
hbase> t.count
hbase> t.count INTERVAL => 100000
hbase> t.count CACHE => 1000
hbase> t.count INTERVAL => 10, CACHE => 1000
hbase> t.count FILTER => "
(QualifierFilter (>=, 'binary:xyz')) AND (TimestampsFilter ( 123, 456))"
hbase> t.count COLUMNS => ['c1', 'c2'], STARTROW => 'abc', STOPROW => 'xyz'
hbase(main):002:0> count 'istepanian:library'
2 row(s)
Took 0.3549 seconds
=> 2
hbase(main):003:0>There are currently two rows in our table (vhugo and jverne).
We use the get command to retrieve the value with different queries.
hbase(main):003:0> get 'istepanian:library', 'vhugo'
COLUMN CELL
author:firstname timestamp=1605626539551, value=Victor
author:lastname timestamp=1605626571926, value=Hugo
book:categ timestamp=1605626539605, value=Po\xC3\xA8mes
book:title timestamp=1605626539575, value=La L\xC3\xA9gende des si\xC3\xA8cles
book:year timestamp=1605626539664, value=1883
1 row(s)
Took 0.0736 seconds
hbase(main):004:0> get 'istepanian:library', 'vhugo','author'
COLUMN CELL
author:firstname timestamp=1605626539551, value=Victor
author:lastname timestamp=1605626571926, value=Hugo
1 row(s)
Took 0.0082 seconds
hbase(main):005:0> get 'istepanian:library', 'vhugo','author:firstname'
COLUMN CELL
author:firstname timestamp=1605626539551, value=Victor
1 row(s)
Took 0.0061 seconds
hbase(main):006:0> get 'istepanian:library', 'jverne', COLUMN=>'book'
COLUMN CELL
book:publisher timestamp=1605626989362, value=Hetzel
book:title timestamp=1605626989392, value=Face au drapeau
book:year timestamp=1605627001246, value=1896
1 row(s)
Took 0.0096 seconds
hbase(main):007:0> get 'istepanian:library', 'jverne', COLUMN=>'book:title'
COLUMN CELL
book:title timestamp=1605626989392, value=Face au drapeau
1 row(s)
Took 0.0059 seconds
hbase(main):008:0> get 'istepanian:library', 'jverne', COLUMN=>['book:title','book:year','book:publisher']
COLUMN CELL
book:publisher timestamp=1605626989362, value=Hetzel
book:title timestamp=1605626989392, value=Face au drapeau
book:year timestamp=1605627001246, value=1896
1 row(s)
Took 0.0071 seconds
hbase(main):009:0> get 'istepanian:library', 'jverne', FILTER=>"ValueFilter(=,'binary:Jules')"
COLUMN CELL
author:firstname timestamp=1605627013567, value=Jules
1 row(s)
Took 0.0530 seconds
hbase(main):010:0>For the given row keys, we observe each cell described with the column/version/value logic. The column is identified with the column family and the column name, the version is identified by the timestamp, and the value is the data contained in the cell.
We will use the scan command to browse the row tuples, similarly to the get command. To get more information about the usage of the scan command, we will check out help "scan".
hbase(main):001:0> help "scan"
Scan a table; pass table name and optionally a dictionary of scanner
specifications. Scanner specifications may include one or more of:
TIMERANGE, FILTER, LIMIT, STARTROW, STOPROW, ROWPREFIXFILTER, TIMESTAMP,
MAXLENGTH, COLUMNS, CACHE, RAW, VERSIONS, ALL_METRICS, METRICS,
REGION_REPLICA_ID, ISOLATION_LEVEL, READ_TYPE, ALLOW_PARTIAL_RESULTS,
BATCH or MAX_RESULT_SIZE
If no columns are specified, all columns will be scanned.
To scan all members of a column family, leave the qualifier empty as in
'col_family'.
The filter can be specified in two ways:
1. Using a filterString - more information on this is available in the
Filter Language document attached to the HBASE-4176 JIRA
2. Using the entire package name of the filter.
If you wish to see metrics regarding the execution of the scan, the
ALL_METRICS boolean should be set to true. Alternatively, if you would
prefer to see only a subset of the metrics, the METRICS array can be
defined to include the names of only the metrics you care about.
Some examples:
hbase> scan 'hbase:meta'
hbase> scan 'hbase:meta', {COLUMNS => 'info:regioninfo'}
hbase> scan 'ns1:t1', {COLUMNS => ['c1', 'c2'], LIMIT => 10, STARTROW => 'xyz'}
hbase> scan 't1', {COLUMNS => ['c1', 'c2'], LIMIT => 10, STARTROW => 'xyz'}
hbase> scan 't1', {COLUMNS => 'c1', TIMERANGE => [1303668804000, 1303668904000]}
hbase> scan 't1', {REVERSED => true}
hbase> scan 't1', {ALL_METRICS => true}
hbase> scan 't1', {METRICS => ['RPC_RETRIES', 'ROWS_FILTERED']}
hbase> scan 't1', {ROWPREFIXFILTER => 'row2', FILTER => "
(QualifierFilter (>=, 'binary:xyz')) AND (TimestampsFilter ( 123, 456))"}
hbase> scan 't1', {FILTER =>
org.apache.hadoop.hbase.filter.ColumnPaginationFilter.new(1, 0)}
hbase> scan 't1', {CONSISTENCY => 'TIMELINE'}
hbase> scan 't1', {ISOLATION_LEVEL => 'READ_UNCOMMITTED'}
hbase> scan 't1', {MAX_RESULT_SIZE => 123456}
For setting the Operation Attributes
hbase> scan 't1', { COLUMNS => ['c1', 'c2'], ATTRIBUTES => {'mykey' => 'myvalue'}}
hbase> scan 't1', { COLUMNS => ['c1', 'c2'], AUTHORIZATIONS => ['PRIVATE','SECRET']}
For experts, there is an additional option -- CACHE_BLOCKS -- which
switches block caching for the scanner on (true) or off (false). By
default it is enabled. Examples:
hbase> scan 't1', {COLUMNS => ['c1', 'c2'], CACHE_BLOCKS => false}
Also for experts, there is an advanced option -- RAW -- which instructs the
scanner to return all cells (including delete markers and uncollected deleted
cells). This option cannot be combined with requesting specific COLUMNS.
Disabled by default. Example:
hbase> scan 't1', {RAW => true, VERSIONS => 10}
There is yet another option -- READ_TYPE -- which instructs the scanner to
use a specific read type. Example:
hbase> scan 't1', {READ_TYPE => 'PREAD'}
Besides the default 'toStringBinary' format, 'scan' supports custom formatting
by column. A user can define a FORMATTER by adding it to the column name in
the scan specification. The FORMATTER can be stipulated:
1. either as a org.apache.hadoop.hbase.util.Bytes method name (e.g, toInt, toString)
2. or as a custom class followed by method name: e.g. 'c(MyFormatterClass).format'.
Example formatting cf:qualifier1 and cf:qualifier2 both as Integers:
hbase> scan 't1', {COLUMNS => ['cf:qualifier1:toInt',
'cf:qualifier2:c(org.apache.hadoop.hbase.util.Bytes).toInt'] }
Note that you can specify a FORMATTER by column only (cf:qualifier). You can set a
formatter for all columns (including, all key parts) using the "FORMATTER"
and "FORMATTER_CLASS" options. The default "FORMATTER_CLASS" is
"org.apache.hadoop.hbase.util.Bytes".
hbase> scan 't1', {FORMATTER => 'toString'}
hbase> scan 't1', {FORMATTER_CLASS => 'org.apache.hadoop.hbase.util.Bytes', FORMATTER => 'toString'}
Scan can also be used directly from a table, by first getting a reference to a
table, like such:
hbase> t = get_table 't'
hbase> t.scan
Note in the above situation, you can still provide all the filtering, columns,
options, etc as described above.
hbase(main):002:0> scan 'istepanian:library'
ROW COLUMN+CELL
jverne column=author:firstname, timestamp=1605627013567, value=Jules
jverne column=author:lastname, timestamp=1605626989336, value=Verne
jverne column=book:publisher, timestamp=1605626989362, value=Hetzel
jverne column=book:title, timestamp=1605626989392, value=Face au drapeau
jverne column=book:year, timestamp=1605627001246, value=1896
vhugo column=author:firstname, timestamp=1605626539551, value=Victor
vhugo column=author:lastname, timestamp=1605626571926, value=Hugo
vhugo column=book:categ, timestamp=1605626539605, value=Po\xC3\xA8mes
vhugo column=book:title, timestamp=1605626539575, value=La L\xC3\xA9gende des si\xC3\xA8cles
vhugo column=book:year, timestamp=1605626539664, value=1883
2 row(s)
Took 0.3744 seconds
hbase(main):003:0> scan 'istepanian:library', {COLUMNS => 'book'}
ROW COLUMN+CELL
jverne column=book:publisher, timestamp=1605626989362, value=Hetzel
jverne column=book:title, timestamp=1605626989392, value=Face au drapeau
jverne column=book:year, timestamp=1605627001246, value=1896
vhugo column=book:categ, timestamp=1605626539605, value=Po\xC3\xA8mes
vhugo column=book:title, timestamp=1605626539575, value=La L\xC3\xA9gende des si\xC3\xA8cles
vhugo column=book:year, timestamp=1605626539664, value=1883
2 row(s)
Took 0.0197 seconds
hbase(main):004:0> scan 'istepanian:library', {COLUMNS => 'book:year'}
ROW COLUMN+CELL
jverne column=book:year, timestamp=1605627001246, value=1896
vhugo column=book:year, timestamp=1605626539664, value=1883
2 row(s)
Took 0.0096 seconds
hbase(main):005:0> We simply use the Ruby Hashes notation to access data per column family (or column family AND column name). To find rows with a row index starting with a specific symbol or a specific symbol range, we can use the STARTROW and STOP keywords; using filters (FILTER), we can also use the RowFilter (or PrefixFilter for a specific value). To get data from specific columns using a filter, we can use FamilyFilter for the column family and QualifierFilter for the column name; to chain filter, we can use the keywords AND or OR. The SingleColumnValueFilter filter can be used to scan cells based on their value for a given column. A complete list of HBase filters can be found in the Apache Documentations (http://hbase.apache.org/devapidocs/org/apache/hadoop/hbase/filter/package-summary.html).
hbase(main):005:0> scan 'istepanian:library', {STARTROW => 'a', STOPROW => 'n', COLUMNS => 'author'}
ROW COLUMN+CELL
jverne column=author:firstname, timestamp=1605627013567, value=Jules
jverne column=author:lastname, timestamp=1605626989336, value=Verne
1 row(s)
Took 0.0386 seconds
hbase(main):006:0> scan 'istepanian:library', {FILTER=>"RowFilter(>=, 'binary:a') AND RowFilter(<=, 'binary:n') AND FamilyFilter(=, 'binary:author')"}
ROW COLUMN+CELL
jverne column=author:firstname, timestamp=1605627013567, value=Jules
jverne column=author:lastname, timestamp=1605626989336, value=Verne
1 row(s)
Took 0.0436 seconds
hbase(main):007:0> scan 'istepanian:library', {FILTER=>"FamilyFilter (=, 'binary:author') AND QualifierFilter (=, 'binary:firstname')"}
ROW COLUMN+CELL
jverne column=author:firstname, timestamp=1605627013567, value=Jules
vhugo column=author:firstname, timestamp=1605626539551, value=Victor
2 row(s)
Took 0.0287 seconds
hbase(main):008:0> scan 'istepanian:library', {FILTER=>"SingleColumnValueFilter('book', 'title', =, 'binary:La Légende des siècles')"}
ROW COLUMN+CELL
vhugo column=author:firstname, timestamp=1605626539551, value=Victor
vhugo column=author:lastname, timestamp=1605626571926, value=Hugo
vhugo column=book:categ, timestamp=1605626539605, value=Po\xC3\xA8mes
vhugo column=book:title, timestamp=1605626539575, value=La L\xC3\xA9gende des si\xC3\xA8cl
es
vhugo column=book:year, timestamp=1605626539664, value=1883
1 row(s)
Took 0.0640 seconds
hbase(main):009:0> scan 'istepanian:library', {FILTER=>"SingleColumnValueFilter('book', 'year', <=, 'binary:1890')"}
ROW COLUMN+CELL
vhugo column=author:firstname, timestamp=1605626539551, value=Victor
vhugo column=author:lastname, timestamp=1605626571926, value=Hugo
vhugo column=book:categ, timestamp=1605626539605, value=Po\xC3\xA8mes
vhugo column=book:title, timestamp=1605626539575, value=La L\xC3\xA9gende des si\xC3\xA8cl
es
vhugo column=book:year, timestamp=1605626539664, value=1883
1 row(s)
Took 0.3437 seconds
hbase(main):010:0> scan 'istepanian:library', {FILTER=>"PrefixFilter('jv') AND ValueFilter(=,'regexstring:[A-Z]([a-z]+ ){2,}')"}
ROW COLUMN+CELL
jverne column=book:title, timestamp=1605626989392, value=Face au drapeau
1 row(s)
Took 0.0244 secondsTo showcase how versions work in HBase, we will overwrite the current values of the rows using successive put operations
hbase(main):001:0> put 'istepanian:library', 'vhugo', 'author:lastname', 'HAGO'
Took 0.0066 seconds
hbase(main):002:0> get 'istepanian:library', 'vhugo', COLUMNS=>'author', VERSIONS=>2
COLUMN CELL
author:firstname timestamp=1605626539551, value=Victor
author:lastname timestamp=1605983481397, value=HAGO
author:lastname timestamp=1605626571926, value=Hugo
1 row(s)
Took 0.0155 seconds
hbase(main):003:0> put 'istepanian:library', 'vhugo', 'author:lastname', 'HUGO'
Took 0.3580 seconds
hbase(main):004:0> get 'istepanian:library', 'vhugo', COLUMNS=>'author', VERSIONS=>2
COLUMN CELL
author:firstname timestamp=1605626539551, value=Victor
author:lastname timestamp=1605984421312, value=HUGO
author:lastname timestamp=1605983481397, value=HAGO
1 row(s)
Took 0.0427 seconds
hbase(main):005:0> put 'istepanian:library', 'vhugo', 'author:firstname', 'Victor Marie'
Took 0.3452 seconds
hbase(main):006:0> put 'istepanian:library', 'vhugo', 'author:lastname', 'Hugo'
Took 0.0064 seconds
hbase(main):007:0> get 'istepanian:library', 'vhugo', 'author'
COLUMN CELL
author:firstname timestamp=1605984517354, value=Victor Marie
author:lastname timestamp=1605984526059, value=Hugo
1 row(s)
Took 0.0356 seconds
hbase(main):008:0> get 'istepanian:library', 'vhugo', COLUMNS=>'author'
COLUMN CELL
author:firstname timestamp=1605984517354, value=Victor Marie
author:lastname timestamp=1605984526059, value=Hugo
1 row(s)
Took 0.0169 seconds
hbase(main):009:0> get 'istepanian:library', 'vhugo', COLUMNS=>'author', VERSIONS=>2
COLUMN CELL
author:firstname timestamp=1605984517354, value=Victor Marie
author:firstname timestamp=1605626539551, value=Victor
author:lastname timestamp=1605984526059, value=Hugo
author:lastname timestamp=1605984421312, value=HUGO
1 row(s)
Took 0.0164 seconds
hbase(main):010:0> As we can see, value are still conserved in memory after being overwritten; values will still be saved after VERSIONS-1 overwrites (VERSION being one the property defined when a table is created), and then forgotten from the database.
To delete only the value for the timestamp of author:name=HUGO, we first check the usage of the deleteall command
hbase(main):001:0> help "deleteall"
Delete all cells in a given row; pass a table name, row, and optionally
a column and timestamp. Deleteall also support deleting a row range using a
row key prefix. Examples:
hbase> deleteall 'ns1:t1', 'r1'
hbase> deleteall 't1', 'r1'
hbase> deleteall 't1', 'r1', 'c1'
hbase> deleteall 't1', 'r1', 'c1', ts1
hbase> deleteall 't1', 'r1', 'c1', ts1, {VISIBILITY=>'PRIVATE|SECRET'}
ROWPREFIXFILTER can be used to delete row ranges
hbase> deleteall 't1', {ROWPREFIXFILTER => 'prefix'}
hbase> deleteall 't1', {ROWPREFIXFILTER => 'prefix'}, 'c1' //delete certain column family in the row ranges
hbase> deleteall 't1', {ROWPREFIXFILTER => 'prefix'}, 'c1', ts1
hbase> deleteall 't1', {ROWPREFIXFILTER => 'prefix'}, 'c1', ts1, {VISIBILITY=>'PRIVATE|SECRET'}
CACHE can be used to specify how many deletes batched to be sent to server at one time, default is 100
hbase> deleteall 't1', {ROWPREFIXFILTER => 'prefix', CACHE => 100}
The same commands also can be run on a table reference. Suppose you had a reference
t to table 't1', the corresponding command would be:
hbase> t.deleteall 'r1', 'c1', ts1, {VISIBILITY=>'PRIVATE|SECRET'}
hbase> t.deleteall {ROWPREFIXFILTER => 'prefix', CACHE => 100}, 'c1', ts1, {VISIBILITY=>'PRIVATE|SECRET'}To select only a specific timestamp, we use the fourth argument of the deleteall operation.
hbase(main):001:0> deleteall 'istepanian:library', 'vhugo', 'author:lastname', 1605984421312
Took 0.0106 seconds
hbase(main):002:0> get 'istepanian:library', 'vhugo', COLUMNS=>'author', VERSIONS=>2
COLUMN CELL
author:firstname timestamp=1605984517354, value=Victor Marie
author:firstname timestamp=1605626539551, value=Victor
author:lastname timestamp=1605984526059, value=Hugo
1 row(s)
Took 0.0107 seconds
hbase(main):002:0> scan 'istepanian:library', {COLUMNS => 'author:firstname'}
ROW COLUMN+CELL
jverne column=author:firstname, timestamp=1605627013567, value=Jules
1 row(s)
Took 0.0457 seconds
hbase(main):003:0> deleteall 'istepanian:library', 'vhugo'
Took 0.0070 seconds
hbase(main):004:0> scan 'istepanian:library', {VERSIONS => 10}
ROW COLUMN+CELL
jverne column=author:firstname, timestamp=1605627013567, value=Jules
jverne column=author:firstname, timestamp=1605626539683, value=Jules
jverne column=author:lastname, timestamp=1605626989336, value=Verne
jverne column=author:lastname, timestamp=1605626539700, value=Verne
jverne column=book:publisher, timestamp=1605626989362, value=Hetzel
jverne column=book:publisher, timestamp=1605626539719, value=Hetzel
jverne column=book:title, timestamp=1605626989392, value=Face au drapeau
jverne column=book:title, timestamp=1605626539736, value=Face au drapeau
jverne column=book:year, timestamp=1605627001246, value=1896
jverne column=book:year, timestamp=1605626539755, value=1896
1 row(s)
Took 0.0320 secondsTo showcase the delete operation, we first check the usage of the command:
hbase(main):005:0> help "delete"
Put a delete cell value at specified table/row/column and optionally
timestamp coordinates. Deletes must match the deleted cell's
coordinates exactly. When scanning, a delete cell suppresses older
versions. To delete a cell from 't1' at row 'r1' under column 'c1'
marked with the time 'ts1', do:
hbase> delete 'ns1:t1', 'r1', 'c1', ts1
hbase> delete 't1', 'r1', 'c1', ts1
hbase> delete 't1', 'r1', 'c1', ts1, {VISIBILITY=>'PRIVATE|SECRET'}
The same command can also be run on a table reference. Suppose you had a reference
t to table 't1', the corresponding command would be:
hbase> t.delete 'r1', 'c1', ts1
hbase> t.delete 'r1', 'c1', ts1, {VISIBILITY=>'PRIVATE|SECRET'}The command will put a new delete flag as the new cell values, making them invisible to scan and get operations. It will "erase" the latest value first.
hbase(main):006:0> scan 'istepanian:library', {VERSIONS => 10}
ROW COLUMN+CELL
jverne column=author:firstname, timestamp=1605627013567, value=Jules
jverne column=author:firstname, timestamp=1605626539683, value=Jules
jverne column=author:lastname, timestamp=1605626989336, value=Verne
jverne column=author:lastname, timestamp=1605626539700, value=Verne
jverne column=book:publisher, timestamp=1605626989362, value=Hetzel
jverne column=book:publisher, timestamp=1605626539719, value=Hetzel
jverne column=book:title, timestamp=1605626989392, value=Face au drapeau
jverne column=book:title, timestamp=1605626539736, value=Face au drapeau
jverne column=book:year, timestamp=1605627001246, value=1896
jverne column=book:year, timestamp=1605626539755, value=1896
1 row(s)
Took 0.0144 seconds
hbase(main):007:0> delete 'istepanian:library', 'jverne', 'author:firstname'
Took 0.0118 seconds
hbase(main):008:0> scan 'istepanian:library', {VERSIONS => 10}
ROW COLUMN+CELL
jverne column=author:firstname, timestamp=1605626539683, value=Jules
jverne column=author:lastname, timestamp=1605626989336, value=Verne
jverne column=author:lastname, timestamp=1605626539700, value=Verne
jverne column=book:publisher, timestamp=1605626989362, value=Hetzel
jverne column=book:publisher, timestamp=1605626539719, value=Hetzel
jverne column=book:title, timestamp=1605626989392, value=Face au drapeau
jverne column=book:title, timestamp=1605626539736, value=Face au drapeau
jverne column=book:year, timestamp=1605627001246, value=1896
jverne column=book:year, timestamp=1605626539755, value=1896
1 row(s)
Took 0.0365 seconds
hbase(main):022:0> delete 'istepanian:library', 'jverne', 'author:firstname'
Took 0.0127 seconds
hbase(main):009:0> scan 'istepanian:library', {VERSIONS => 10}
ROW COLUMN+CELL
jverne column=author:lastname, timestamp=1605626989336, value=Verne
jverne column=author:lastname, timestamp=1605626539700, value=Verne
jverne column=book:publisher, timestamp=1605626989362, value=Hetzel
jverne column=book:publisher, timestamp=1605626539719, value=Hetzel
jverne column=book:title, timestamp=1605626989392, value=Face au drapeau
jverne column=book:title, timestamp=1605626539736, value=Face au drapeau
jverne column=book:year, timestamp=1605627001246, value=1896
jverne column=book:year, timestamp=1605626539755, value=1896
1 row(s)
Took 0.0256 seconds As we can see in the help menu, there is a disable command that allows us to disable a table before deleting it. Then, to delete the table, we use the drop command, just like in most DBMS software.
hbase(main):005:0> disable 'istepanian:library'
Took 1.1565 seconds
hbase(main):006:0> drop 'istepanian:library'
Took 0.4755 seconds
hbase(main):07:0> list_namespace_tables 'istepanian'
TABLE
0 row(s)
Took 0.0113 seconds
=> []To insert our CSV file into a HBase table, we will use shell pipes and a simple Python script to convert the raw line-by-line data of the CSV files into HBase commands that will insert the table elements one by one. The first line that the script will output will create the table, and the next outputs will put the column values for each row into the table. We also need to avoid the first line of the CSV files, the header that contains the field names (we will hardcode the field names into script, as it will have use only for this specific case). Here is what such a script would look like:
#!/ usr/bin/env python
""" script.py """
import sys
sys.stdout.write("create \"istepanian:trees\", {NAME => \"species\", VERSIONS => 2}, {NAME => \"information\", VERSIONS => 2}, {NAME => \"address\", VERSIONS => 2};\n")
count = 0
for line in sys.stdin:
if count > 0:
fields = line.split(";")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"species:GENRE\", \"" + fields[2] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"species:ESPECE\", \"" + fields[3] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"species:FAMILLE\", \"" + fields[4] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"species:NOM COMMUN\", \"" + fields[9] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"species:VARIETE\", \"" + fields[10] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"information:ANNEE PLANTATION\", \"" + fields[2] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"information:HAUTEUR\", \"" + fields[2] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"information:CIRCONFERENCE\", \"" + fields[2] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"address:GEOPOINT\", \"" + fields[2] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"address:ARRONDISSEMENT\", \"" + fields[2] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"address:ADRESSE\", \"" + fields[2] + "\";\n")
sys.stdout.write("put \"istepanian:trees\", \"" + fields[11] + "\", \"address:NOM_EV\", \"" + fields[2] + "\";\n")
count += 1We then pipe a cat of our trees.csv file into the script, and pipe the script's output into the HBase Shell (hdfs dfs -cat trees.csv | python script.py | hbase shell); we then scan our newly created istepanian:trees table to see that the script worked.
-sh-4.2$ hdfs dfs -cat trees.csv | python script.py | hbase shell
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/hdp/3.1.5.0-152/hadoop/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/3.1.5.0-152/hbase/lib/client-facing-thirdparty/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
HBase Shell
Use "help" to get list of supported commands.
Use "exit" to quit this interactive shell.
For Reference, please visit: http://hbase.apache.org/2.0/book.html#shell
Version 2.1.6.3.1.5.0-152, rUnknown, Thu Dec 12 20:16:57 UTC 2019
Took 0.0035 seconds
create "istepanian:trees", {NAME => "species", VERSIONS => 2}, {NAME => "information", VERSIONS => 2}, {NAME => "address", VERSIONS => 2};
put "istepanian:trees", "6", "species:GENRE", "Maclura";
put "istepanian:trees", "6", "species:ESPECE", "pomifera";
put "istepanian:trees", "6", "species:FAMILLE", "Moraceae";
put "istepanian:trees", "6", "species:NOM COMMUN", "Oranger des Osages";
put "istepanian:trees", "6", "species:VARIETE", "";
put "istepanian:trees", "6", "information:ANNEE PLANTATION", "1935";
put "istepanian:trees", "6", "information:HAUTEUR", "13.0";
put "istepanian:trees", "6", "information:CIRCONFERENCE", "";
put "istepanian:trees", "6", "address:GEOPOINT", "(48.857140829, 2.29533455314)";
put "istepanian:trees", "6", "address:ARRONDISSEMENT", "7";
put "istepanian:trees", "6", "address:ADRESSE", "Quai Branly, avenue de La Motte-Piquet, avenue de la Bourdonnais, avenue de Suffren";
put "istepanian:trees", "6", "address:NOM_EV", "Parc du Champs de Mars
";
...
put "istepanian:trees", "91", "species:GENRE", "Acer";
put "istepanian:trees", "91", "species:ESPECE", "opalus";
put "istepanian:trees", "91", "species:FAMILLE", "Sapindaceae";
put "istepanian:trees", "91", "species:NOM COMMUN", "Erable d'Italie";
put "istepanian:trees", "91", "species:VARIETE", "";
put "istepanian:trees", "91", "information:ANNEE PLANTATION", "1870";
put "istepanian:trees", "91", "information:HAUTEUR", "15.0";
put "istepanian:trees", "91", "information:CIRCONFERENCE", "160.0";
put "istepanian:trees", "91", "address:GEOPOINT", "(48.8302532096, 2.41400587444)";
put "istepanian:trees", "91", "address:ARRONDISSEMENT", "12";
put "istepanian:trees", "91", "address:ADRESSE", "Ile de Bercy";
put "istepanian:trees", "91", "address:NOM_EV", "Bois de Vincennes (Ile de Bercy)
";
Created table istepanian:trees
Took 2.5275 seconds
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-sh-4.2$ hbase shell
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/hdp/3.1.5.0-152/hadoop/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/3.1.5.0-152/hbase/lib/client-facing-thirdparty/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
HBase Shell
Use "help" to get list of supported commands.
Use "exit" to quit this interactive shell.
For Reference, please visit: http://hbase.apache.org/2.0/book.html#shell
Version 2.1.6.3.1.5.0-152, rUnknown, Thu Dec 12 20:16:57 UTC 2019
Took 0.0026 seconds
hbase(main):001:0> scan 'istepanian:trees', {'LIMIT' => 5}
ROW COLUMN+CELL
1 column=address:ADRESSE, timestamp=1606163503607, value=Rue du
Temple, rue de Bretagne, Rue Perr\xC3\xA9e, rue Eug\xC3\xA8ne-
Spuller
1 column=address:ARRONDISSEMENT, timestamp=1606163503605, value=
3
1 column=address:GEOPOINT, timestamp=1606163503602, value=(48.86
48376291, 2.36062929978)
1 column=address:NOM_EV, timestamp=1606163503609, value=Square d
u Temple\x0A
1 column=information:ANNEE PLANTATION, timestamp=1606163503595,
value=1882
1 column=information:CIRCONFERENCE, timestamp=1606163503600, val
ue=210.0
1 column=information:HAUTEUR, timestamp=1606163503597, value=20.
0
1 column=species:ESPECE, timestamp=1606163503585, value=colurna
1 column=species:FAMILLE, timestamp=1606163503588, value=Betulac
eae
1 column=species:GENRE, timestamp=1606163503583, value=Corylus
1 column=species:NOM COMMUN, timestamp=1606163503590, value=Nois
etier de Byzance
1 column=species:VARIETE, timestamp=1606163503593, value=
10 column=address:ADRESSE, timestamp=1606163502051, value=Bouleva
rd de Courcelles, avenue V\xE2\x80\x9Alasquez, avenue Van-Dyck
, avenue Ruysdael
10 column=address:ARRONDISSEMENT, timestamp=1606163502048, value=
8
10 column=address:GEOPOINT, timestamp=1606163502046, value=(48.87
92159582, 2.30640768208)
10 column=address:NOM_EV, timestamp=1606163502053, value=Parc Mon
ceau\x0A
10 column=information:ANNEE PLANTATION, timestamp=1606163502039,
value=1879
10 column=information:CIRCONFERENCE, timestamp=1606163502043, val
ue=283.0
10 column=information:HAUTEUR, timestamp=1606163502041, value=22.
0
10 column=species:ESPECE, timestamp=1606163502029, value=biloba
10 column=species:FAMILLE, timestamp=1606163502031, value=Ginkgoa
ceae
10 column=species:GENRE, timestamp=1606163502026, value=Ginkgo
10 column=species:NOM COMMUN, timestamp=1606163502034, value=Arbr
e aux quarante \xC3\xA9cus
10 column=species:VARIETE, timestamp=1606163502036, value=
11 column=address:ADRESSE, timestamp=1606163500902, value=Cours-l
a-Reine, avenue Franklin-D.-Roosevelt, avenue Matignon, avenue
Gabriel
11 column=address:ARRONDISSEMENT, timestamp=1606163500895, value=
8
11 column=address:GEOPOINT, timestamp=1606163500890, value=(48.86
85686134, 2.31331809304)
11 column=address:NOM_EV, timestamp=1606163500907, value=Jardin d
es Champs Elys\xC3\xA9es\x0A
11 column=information:ANNEE PLANTATION, timestamp=1606163500876,
value=1854
11 column=information:CIRCONFERENCE, timestamp=1606163500885, val
ue=195.0
11 column=information:HAUTEUR, timestamp=1606163500880, value=20.
0
11 column=species:ESPECE, timestamp=1606163500855, value=decurren
s
11 column=species:FAMILLE, timestamp=1606163500861, value=Cupress
aceae
11 column=species:GENRE, timestamp=1606163500851, value=Calocedru
s
11 column=species:NOM COMMUN, timestamp=1606163500867, value=C\xC
3\xA8dre \xC3\xA0 encens
11 column=species:VARIETE, timestamp=1606163500872, value=
12 column=address:ADRESSE, timestamp=1606163502082, value=Cours-l
a-Reine, avenue Franklin-D.-Roosevelt, avenue Matignon, avenue
Gabriel
12 column=address:ARRONDISSEMENT, timestamp=1606163502079, value=
8
12 column=address:GEOPOINT, timestamp=1606163502076, value=(48.86
69690843, 2.31951408752)
12 column=address:NOM_EV, timestamp=1606163502084, value=Jardin d
es Champs Elys\xC3\xA9es\x0A
12 column=information:ANNEE PLANTATION, timestamp=1606163502068,
value=1850
12 column=information:CIRCONFERENCE, timestamp=1606163502073, val
ue=320.0
12 column=information:HAUTEUR, timestamp=1606163502071, value=20.
0
12 column=species:ESPECE, timestamp=1606163502058, value=giganteu
m
12 column=species:FAMILLE, timestamp=1606163502060, value=Taxodia
ceae
12 column=species:GENRE, timestamp=1606163502056, value=Sequoiade
ndron
12 column=species:NOM COMMUN, timestamp=1606163502063, value=S\xC
3\xA9quoia g\xC3\xA9ant
12 column=species:VARIETE, timestamp=1606163502066, value=
13 column=address:ADRESSE, timestamp=1606163503345, value=Cours-l
a-Reine, avenue Franklin-D.-Roosevelt, avenue Matignon, avenue
Gabriel
13 column=address:ARRONDISSEMENT, timestamp=1606163503343, value=
8
13 column=address:GEOPOINT, timestamp=1606163503340, value=(48.86
52536076, 2.31333976248)
13 column=address:NOM_EV, timestamp=1606163503347, value=Jardin d
es Champs Elys\xC3\xA9es\x0A
13 column=information:ANNEE PLANTATION, timestamp=1606163503333,
value=1900
13 column=information:CIRCONFERENCE, timestamp=1606163503338, val
ue=480.0
13 column=information:HAUTEUR, timestamp=1606163503336, value=20.
0
13 column=species:ESPECE, timestamp=1606163503324, value=oriental
is
13 column=species:FAMILLE, timestamp=1606163503326, value=Platana
ceae
13 column=species:GENRE, timestamp=1606163503322, value=Platanus
13 column=species:NOM COMMUN, timestamp=1606163503329, value=Plat
ane d'Orient
13 column=species:VARIETE, timestamp=1606163503331, value=
5 row(s)
Took 0.3646 seconds
hbase(main):002:0> Our script worked as expected.