Hive
Hive source connector
Description
Read data from Hive.
Key features
Read all the data in a split in a pollNext call. What splits are read will be saved in snapshot.
Options
table_name
string
yes
-
metastore_uri
string
yes
-
krb5_path
string
no
/etc/krb5.conf
kerberos_principal
string
no
-
kerberos_keytab_path
string
no
-
hdfs_site_path
string
no
-
hive_site_path
string
no
-
hive.hadoop.conf
Map
no
-
hive.hadoop.conf-path
string
no
-
read_partitions
list
no
-
read_columns
list
no
-
compress_codec
string
no
none
common-options
no
-
table_name [string]
Target Hive table name eg: db1.table1
metastore_uri [string]
Hive metastore uri
hdfs_site_path [string]
The path of hdfs-site.xml, used to load ha configuration of namenodes
hive.hadoop.conf [map]
Properties in hadoop conf('core-site.xml', 'hdfs-site.xml', 'hive-site.xml')
hive.hadoop.conf-path [string]
The specified loading path for the 'core-site.xml', 'hdfs-site.xml', 'hive-site.xml' files
read_partitions [list]
The target partitions that user want to read from hive table, if user does not set this parameter, it will read all the data from hive table.
Tips: Every partition in partitions list should have the same directory depth. For example, a hive table has two partitions: par1 and par2, if user sets it like as the following: read_partitions = [par1=xxx, par1=yyy/par2=zzz], it is illegal
krb5_path [string]
The path of krb5.conf, used to authentication kerberos
kerberos_principal [string]
The principal of kerberos authentication
kerberos_keytab_path [string]
The keytab file path of kerberos authentication
read_columns [list]
The read column list of the data source, user can use it to implement field projection.
compress_codec [string]
The compress codec of files and the details that supported as the following shown:
txt:
lzononejson:
lzononecsv:
lzononeorc/parquet: automatically recognizes the compression type, no additional settings required.
common options
Source plugin common parameters, please refer to Source Common Options for details
Example
Example 1: Single table
Example 2: Multiple tables
Hive on s3
Run the case.
Hive on oss
Run the case.
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