Spark on HBase Overview and Basic Applications¶
Scenario¶
Spark on HBase allows users to query HBase tables in Spark SQL and to store data for HBase tables by using the Beeline tool. You can use HBase APIs to create, read data from, and insert data into tables.
Procedure¶
Log in to Manager and choose Cluster > Name of the desired cluster > Cluster Properties to check whether the cluster is in security mode.
Choose Cluster > Name of the desired cluster > Service > Spark2x > Configuration > All Configurations > JDBCServer2x > Default, and modify the following parameter.
Table 1 Parameter list 1¶ Parameter
Default Value
Changed To
spark.yarn.security.credentials.hbase.enabled
false
true
Note
To ensure that Spark2x can access HBase for a long time, do not modify the following parameters of the HBase and HDFS services:
dfs.namenode.delegation.token.renew-interval
dfs.namenode.delegation.token.max-lifetime
hbase.auth.key.update.interval
hbase.auth.token.max.lifetime (The value is fixed to 604800000 ms, that is, 7 days.)
If the preceding parameter configuration must be modified based on service requirements, ensure that the value of the HDFS parameter dfs.namenode.delegation.token.renew-interval is not greater than the values of the HBase parameters hbase.auth.key.update.interval, hbase.auth.token.max.lifetime, and dfs.namenode.delegation.token.max-lifetime.
Choose SparkResource2x > Default and modify the following parameters.
Table 2 Parameter list 2¶ Parameter
Default Value
Changed To
spark.yarn.security.credentials.hbase.enabled
false
true
Restart the Spark2x service for the configuration to take effect.
Note
To use the Spark on HBase function on the Spark2x client, you need to download and install the Spark2x client again.
On the Spark2x client, use the spark-sql or spark-beeline connection to query tables created by Hive on HBase. You can create an HBase table by running SQL commands or create an external table to associate the HBase table. Before creating tables, ensure that HBase tables exist in HBase. The HBase table table1 is used as an example.
Run the following commands to create the HBase table using the Beeline tool:
create table hbaseTable
(
id string,
name string,
age int
)
using org.apache.spark.sql.hbase.HBaseSource
options(
hbaseTableName "table1",
keyCols "id",
colsMapping "
name=cf1.cq1,
age=cf1.cq2
");
Note
hbaseTable: name of the created Spark table
id string,name string, age int: field name and field type of the Spark table
table1: name of the HBase table
id: row key column name of the HBase table
name=cf1.cq1, age=cf1.cq2: mapping between columns in the Spark table and columns in the HBase table. The name column of the Spark table maps the cq1 column in the cf1 column family of the HBase table, and the age column of the Spark table maps the cq2 column in the cf1 column family of the HBase table.
Run the following command to import data to the HBase table using a CSV file:
hbase org.apache.hadoop.hbase.mapreduce.ImportTsv -Dimporttsv.separator="," -Dimporttsv.columns=HBASE_ROW_KEY,cf1:cq1,cf1:cq2,cf1:cq3,cf1:cq4,cf1:cq5 table1 /hperson
Where table1 indicates the name of the HBase table, and /hperson indicates the path where the CSV file is stored.
Run the following command to query data in spark-sql or spark-beeline, where hbaseTable is the corresponding Spark table name: The command is as follows:
select * from hbaseTable;