Using BulkLoad to Import Data to HBase in Batches
When batch importing a large amount of data to HBase, you have many choices, for example, calling the put method of HBase to insert data or using MapReduce to load data from HDFS. However, the two methods cause high pressure on the RegionServer and consume a large number of CPU and network resources because of frequent flush, compact, and split operations of HBase, thereby resulting in low efficiency.
This practice describes how to import local data to HBase in batches using BulkLoad after you create an MRS cluster. This method greatly improves the write efficiency and reduces the write pressure on RegionServer nodes.
You can get started by reading the following topics:
- Creating an MRS Offline Query Cluster
- Importing Local Data to HDFS
- Creating an HBase Table
- Generating an HFile and Importing It to HBase
Scenario
BulkLoad uses MapReduce jobs to directly convert data into HFiles that comply with the internal data format of HBase, and then loads the generated StoreFiles to the corresponding nodes in a cluster. This method requires no flush, compact, or split operations, occupies no region resources, and generates little write requests. Fewer CPU and network resources are required.
- Large amounts of data needs to be loaded to HBase in the one-off manner.
- When data is loaded to HBase, requirements on reliability are not high and WAL files do not need to be generated.
- When the put method is used to load large amounts of data to HBase, data loading and query will be slow.
- The size of an HFile generated after data loading is similar to the size of HDFS blocks.
Creating an MRS Offline Query Cluster
- Go to the Buy Cluster page.
- Click the Quick Config tab and set configuration parameters.
Table 1 Software configurations Parameter
Value
Region
EU-Dublin
Billing Mode
Pay-per-use
Cluster Name
MRS_hbase
Version Type
Normal
Cluster Version
MRS 3.1.0
Component
HBase Query Cluster
AZ
AZ1
Enterprise Project
default
VPC
vpc-01
Subnet
subnet-01
Kerberos Authentication
Toggle the slider on.
Username
root/admin
Password
Set the password for logging in to the cluster management page and ECS node, for example, Test!@12345.
Confirm Password
Enter the password again.
Secure Communications
Select Enable.
Figure 1 Creating an HBase query cluster
- Click Buy Now and wait until the MRS cluster is created.
Importing Local Data to HDFS
- Prepare a student information file info.txt on the local host.
The fields include student ID, name, birthday, gender, and address. An example file is as follows:
20200101245, Zhang xx, 20150324, Male, City 1 20200101246, Li xx, 20150202, Male, City 2 20200101247, Yang xx, 20151101, Female, City 3 20200101248, Chen xx, 20150218, Male, City 4 20200101249, Li xx, 20150801, Female, City 5 20200101250, Wang xx, 20150315, Male, City 6 20200101251, Li xx, 20151201, Male, City 7 20200101252, Sun xx, 20150916, Female, City 8 20200101253, Lin xx, 20150303, Male, City 9
- Log in to the OBS console, click Create Bucket, set the following parameters, and click Create Now.
Table 2 Bucket parameters Parameter
Value
Region
EU-Dublin
Bucket Name
mrs-hbase
Data Redundancy Policy
Single-AZ storage
Default Storage Class
Standard
Bucket Policy
Private
Default Encryption
Disabled
Direct Reading
Disable
Enterprise Project
default
Tags
-
After the bucket is created, click the bucket name. In the navigation pane on the left, choose Objects and click Upload Object to upload the data file.
Figure 2 Uploading an object
- Switch back to the MRS console and click the name of the created MRS cluster. On the Dashboard page, click Synchronize next to IAM User Sync. The synchronization takes about five minutes.
- Upload the data file to the HDFS.
- On the Files page, click the HDFS File List and go to the data storage directory, for example, /tmp/test.
The /tmp/test directory is only an example. You can use any directory on the page or create a new one.
- Click Import Data.
- OBS Path: Find the info.txt file in the created OBS bucket and click Yes.
- HDFS Path: Select an HDFS path, for example, /tmp/test, and click Yes.
- Click OK and wait until the data file is imported.
Figure 3 Importing data
- On the Files page, click the HDFS File List and go to the data storage directory, for example, /tmp/test.
Creating an HBase Table
- Log in to FusionInsight Manager of the cluster (if no elastic IP address is available, purchase one), create a user named hbasetest, and bind it to the user group supergroup and role System_administrator.
- Download the cluster client, and install it, for example, in the /opt/client directory of the active master node.
You can also use the cluster client provided by the Master node. The installation directory is /opt/Bigdata/client.
- Run the following commands to bind an elastic IP address to the active Master node, log in to the active Master node as user root, go to the directory where the client is located, and authenticate the user.
cd /opt/client
source bigdata_env
kinit hbasetest
- Run the hbase shell command to go to the HBase shell page.
Plan the table name, rowkey, column family, and column of the HBase data table based on the imported data. Ensure that the rowkey is pre-split during table creation.
Run the following command to create the student_info table:
create 'student_info', {NAME => 'base',COMPRESSION => 'SNAPPY', DATA_BLOCK_ENCODING => 'FAST_DIFF'},SPLITS => ['1','2','3','4','5','6','7','8']
- NAME => 'base': Column family name of the HBase table
- COMPRESSION: Compression mode
- DATA_BLOCK_ENCODING: encoding algorithm
- SPLITS: Region pre-splitting
- Run the following command to check whether the table is created and exit the HBase shell page:
Generating an HFile and Importing It to HBase
- Create a custom template file, for example, /opt/configuration_index.xml. You can obtain the template file example from Client installation directory/HBase/hbase/conf/index_import.xml.template.
vi /opt/configuration_index.xml
An example template file is as follows:
<?xml version="1.0" encoding="UTF-8"?> <configuration> <!--The value of column_num must be consistent with the number of columns in the data file: 5 columns --> <import column_num="5" id="first"> <columns> <column type="string" index="1">P_ID</column> <column type="string" index="2">P_NAME</column> <column type="string" index="3">P_BIRTH</column> <column type="string" index="4">P_GENDER</column> <column type="string" index="5">P_DISTRICT</column> </columns> <!--reverse(P_BIRTH): Reverse the birth date to avoid hotspotting. --> <!--substring(P_NAME,0,1): Filter out the student information based on the last name. --> <!--substring(P_ID,0,6): Filter out the student information based on the first six digits of a student ID. --> <rowkey> reverse(P_BIRTH)+'_'+substring(P_NAME,0,1)+'_'+substring(P_ID,0,6) </rowkey> <qualifiers> <!--The specified family must correspond to the column family of the table. --> <normal family="base"> <qualifier column="P_ID">H_ID</qualifier> <qualifier column="P_NAME">H_NAME</qualifier> <qualifier column="P_BIRTH">H_BIRTH</qualifier> <qualifier column="P_GENDER">H_GENDER</qualifier> <qualifier column="P_DISTRICT">H_DISTRICT</qualifier> </normal> </qualifiers> </import> </configuration>
- Run the following commands to generate an HFile file:
hbase com.huawei.hadoop.hbase.tools.bulkload.ImportData -Dimport.separator=',' -Dimport.hfile.output=/tmp/test/hfile /opt/configuration_index.xml student_info /tmp/test/info.txt
- -Dimport.separator: indicates a separator.
- -Dimport.hfile.output: indicates the output path of the execution result.
- /opt/configuration_index.xml: indicates a custom template file.
- student_info: indicates the name of the HBase table to be operated.
- /tmp/test/info.txt: indicates the HDFS data directory to which data is to be uploaded in batches.
- com.huawei.hadoop.hbase.tools.bulkload.IndexImportData: indicates IndexImportData used to create a secondary index during data import. If no secondary index needs to be created, ImportData is used.
After the MapReduce job is successfully executed, run the following command to an HFile file in the output path.
hdfs dfs -ls /tmp/test/hfile
Found 2 items -rw-r--r-- 3 hbasetest hadoop 0 2021-05-14 11:39 /tmp/test/hfile/_SUCCESS drwxr-xr-x - hbasetest hadoop 0 2021-05-14 11:39 /tmp/test/hfile/base
- Run the following command to import the HFile to the HBase table:
hbase org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles /tmp/test/hfile student_info
- Run the following commands to go to the HBase shell page and view the table content:
scan 'student_info', {FORMATTER => 'toString'}
ROW COLUMN+CELL 10115102_Yang_202001 column=base:H_BIRTH, timestamp=2021-05-14T15:28:56.755, value=20151101 10115102_Yang_202001 column=base:H_DISTRICT, timestamp=2021-05-14T15:28:56.755, value=City3 10115102_Yang_202001 column=base:H_GENDER, timestamp=2021-05-14T15:28:56.755, value=female 10115102_Yang_202001 column=base:H_ID, timestamp=2021-05-14T15:28:56.755, value=20200101247 10115102_Yang_202001 column=base:H_NAME, timestamp=2021-05-14T15:28:56.755, value=Yang xx 10215102_Li_202001 column=base:H_BIRTH, timestamp=2021-05-14T15:28:56.755, value=20151201 10215102_Li_202001 column=base:H_DISTRICT, timestamp=2021-05-14T15:28:56.755, value=City7 ...
- Analyze and process data based on the upper-layer applications of the big data platform after data is imported to the cluster.
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