Help Center/ DataArts Studio/ User Guide/ DataArts Migration/ Tutorials/ Migrating Data from MySQL to MRS Hive
Updated on 2022-09-23 GMT+08:00

Migrating Data from MySQL to MRS Hive

MRS provides enterprise-level big data clusters on the cloud. It contains HDFS, Hive, and Spark components and is applicable to massive data analysis of enterprises.

Hive supports SQL to help users perform extraction, transformation, and loading (ETL) operations on large-scale data sets. Query on large-scale data sets takes a long time. In many scenarios, you can create Hive partitions to reduce the total amount of data to be scanned each time. This significantly improves query performance.

Hive partitions are implemented by using the HDFS subdirectory function. Each subdirectory contains the column names and values of each partition. If there are multiple partitions, many HDFS subdirectories exist. It is not easy to load external data to each partition of the Hive table without relying on tools. With CDM, you can easily load data of the external data sources (relational databases, object storage services, and file system services) to Hive partition tables.

This section describes how to migrate data from the MySQL database to the MRS Hive partition table.

Scenario

Suppose that there is a trip_data table in the MySQL database. The table stores cycling records such as the start time, end time, start sites, end sites, and rider IDs. For details about the fields in the trip_data table, see Figure 1.

Figure 1 MySQL table fields

The following describes how to use CDM to import the trip_data table in the MySQL database to the MRS Hive partition table. The procedure is as follows:

  1. Creating a Hive Partition Table on MRS Hive
  2. Creating a CDM Cluster and Binding an EIP to the Cluster
  3. Creating a MySQL Link
  4. Creating a Hive Link
  5. Creating a Migration Job

Prerequisites

  • MRS is available.
  • You have obtained the IP address, port, database name, username, and password for connecting to the MySQL database. In addition, the user must have the read and write permissions on the MySQL database.
  • You have uploaded a MySQL database driver by following the instructions provided in Managing Drivers.

Creating a Hive Partition Table on MRS Hive

On MRS Hive, run the following SQL statement to create a Hive partition table named trip_data with three new fields y, ym, and ymd used as partition fields. The SQL statement is as follows:
1
create table trip_data(TripID int,Duration int,StartDate timestamp,StartStation varchar(64),StartTerminal int,EndDate timestamp,EndStation varchar(64),EndTerminal int,Bike int,SubscriberType varchar(32),ZipCodev varchar(10))partitioned by (y int,ym int,ymd int);

The trip_data partition table has three partition fields: year, year and month, and year, month, and date of the start time of a ride. For example, if the start time of a ride is 2018/5/11 9:40, the record is saved in the trip_data/2018/201805/20180511 partition. When the records in the trip_data table are summarized, only part of the data needs to be scanned, greatly improving the performance.

Creating a CDM Cluster and Binding an EIP to the Cluster

  1. If is an independent CDM service, create a CDM cluster by following the instructions provided in Creating a Cluster. If is used as a CDM component of DataArts Studio, create a CDM cluster by following the instructions provided in Creating a Cluster.

    The key configurations are as follows:

    • The flavor of the CDM cluster is selected based on the amount of data to be migrated. Generally, cdm.medium meets the requirements for most migration scenarios.
    • The CDM and MRS clusters must be in the same VPC, subnet, and security group.

  2. After the CDM cluster is created, on the Cluster Management page, click Bind EIP in the Operation column to bind an EIP to the cluster. The CDM cluster uses the EIP to access MySQL.

    Figure 2 Cluster list

    If SSL encryption is configured for the access channel of a local data source, CDM cannot connect to the data source using the EIP.

Creating a MySQL Link

  1. On the Cluster Management page, locate a cluster and click Job Management in the Operation column. On the displayed page, click the Links tab and then Create Link.

    Figure 3 Selecting a connector

  2. Select MySQL and click Next. On the page that is displayed, configure MySQL link parameters.

    Figure 4 Creating a MySQL link

    Click Show Advanced Attributes and set optional parameters. For details, see Link to Relational Databases. Retain the default values of the optional parameters and configure the mandatory parameters according to Table 1.

    Table 1 MySQL link parameters

    Parameter

    Description

    Example Value

    Name

    Unique link name

    mysqllink

    Database Server

    IP address or domain name of the MySQL database server

    192.168.1.110

    Port

    MySQL database port

    3306

    Database Name

    Name of the MySQL database

    sqoop

    Username

    User who has the read, write, and delete permissions on the MySQL database

    admin

    Password

    Password of the user

    -

    Use Local API

    Whether to use the local API of the database for acceleration. (The system attempts to enable the local_infile system variable of the MySQL database.)

    Yes

    Use Agent

    Whether to extract data from the data source through an agent

    Yes

    local_infile Character Set

    When using local_infile to import data to MySQL, you can configure the encoding format.

    utf8

    Driver Version

    A driver version that adapts to MySQL

    -

    Agent

    Click Select to select the agent created in Connecting to an Agent.

    -

    Fetch Size

    (Optional) Displayed when you click Show Advanced Attributes.

    Number of rows obtained by each request. Set this parameter based on the data source and the job's data size. If the value is either too large or too small, the job may run for a long time.

    1000

    Commit Size

    (Optional) Displayed when you click Show Advanced Attributes.

    Number of records submitted each time. Set this parameter based on the data destination and the job's data size. If the value is either too large or too small, the job may run for a long time.

    1000

    Link Attributes

    Custom attributes of the link

    useCompression=true

    Reference Sign

    Delimiter used to separate referenced table names or column names This parameter is left blank by default.

    '

    Batch Size

    Number of rows written each time. It should be less than Commit Size. When the number of rows written reaches the value of Commit Size, the rows will be committed to the database.

    100

  3. Click Save. The Link Management page is displayed.

    If an error occurs during the saving, the security settings of the MySQL database are incorrect. In this case, you need to enable the EIP of the CDM cluster to access the MySQL database.

Creating a Hive Link

  1. Click Job Management in the Operation column of the CDM cluster. On the displayed page, click the Links tab and then Create Link. The Select Connector page is displayed.

    Figure 5 Selecting a connector type

  2. Select MRS Hive and click Next to configure parameters for the MRS Hive link.

    Figure 6 Creating an MRS Hive link

    Table 2 describes the parameters. You can configure the parameters according to the actual situation.

    Table 2 MRS Hive link parameters

    Parameter

    Description

    Example Value

    Name

    Link name, which should be defined based on the data source type, so it is easier to remember what the link is for

    hivelink

    Manager IP

    Floating IP address of MRS Manager. Click Select next to the Manager IP text box to select an MRS cluster. CDM automatically fills in the authentication information.

    127.0.0.1

    Authentication Method

    Authentication method used for accessing MRS
    • SIMPLE: Select this for non-security mode.
    • KERBEROS: Select this for security mode.

    SIMPLE

    HIVE Version

    Set this to the Hive version on the server.

    HIVE_3_X

    Username

    If Authentication Method is set to KERBEROS, you must provide the username and password used for logging in to MRS Manager. If you need to create a snapshot when exporting a directory from HDFS, the user configured here must have the administrator permission on HDFS.

    To create a data connection for an MRS security cluster, do not use user admin. The admin user is the default management page user and cannot be used as the authentication user of the security cluster. You can create an MRS user and set Username and Password to the username and password of the created MRS user when creating an MRS data connection.
    NOTE:
    • If the CDM cluster version is 2.9.0 or later and the MRS cluster version is 3.1.0 or later, the created user must have the permissions of the Manager_viewer role to create links on CDM. To perform operations on databases, tables, and columns of an MRS component, you also need to add the database, table, and column permissions of the MRS component to the user by following the instructions in the MRS documentation.
    • If the CDM cluster version is earlier than 2.9.0 or the MRS cluster version is earlier than 3.1.0, the created user must have the permissions of Manager_administrator or System_administrator to create links on CDM.
    • A user with only the Manager_tenant or Manager_auditor permission cannot create connections.

    cdm

    Password

    Password used for logging in to MRS Manager

    -

    OBS storage support

    The server must support OBS storage. When creating a Hive table, you can store the table in OBS.

    No

    Run Mode

    This parameter is used only when the Hive version is HIVE_3_X. Possible values are:
    • EMBEDDED: The link instance runs with CDM. This mode delivers better performance.
    • Standalone: The link instance runs in an independent process. If CDM needs to connect to multiple Hadoop data sources (MRS, Hadoop, or CloudTable) with both Kerberos and Simple authentication modes, select STANDALONE or configure different agents.

      Note: The STANDALONE mode is used to solve the version conflict problem. If the connector versions of the source and destination ends of the same link are different, a JAR file conflict occurs. In this case, you need to place the source or destination end in the STANDALONE process to prevent the migration failure caused by the conflict.

    EMBEDDED

    Check Hive JDBC Connectivity

    Whether to check the Hive JDBC connectivity

    No

    Use Cluster Config

    You can use the cluster configuration to simplify parameter settings for the Hadoop connection.

    No

    Cluster Config Name

    This parameter is valid only when Use Cluster Config is set to Yes. Select a cluster configuration that has been created.

    For details, see Managing Cluster Configurations.

    hive_01

  3. Click Save. The Link Management page is displayed.

Creating a Migration Job

  1. Choose Table/File Migration > Create Job to create a data migration job. Figure 7 illustrates how to create a migration job.

    Figure 7 Creating a job for migrating data from MySQL to Hive

    Set Clear Data Before Import to Yes, so that the data in the Hive table will be cleared before data import.

  2. After the parameters are configured, click Next. The Map Field tab page is displayed. See Figure 8.

    Map the fields of the MySQL table and Hive table. The Hive table has three more fields y, ym, and ymd than the MySQL table, which are the Hive partition fields. Because the fields of the source table cannot be directly mapped to the destination table, you need to configure an expression to extract data from the StartDate field in the source table.

    Figure 8 Hive field mapping

  3. Click to display the Converter List dialog box, and then choose Create Converter > Expression conversion. See Figure 9.

    The expressions for the y, ym, and ymd fields are as follows:

    DateUtils.format(DateUtils.parseDate(row[2],"yyyy-MM-dd HH:mm:ss.SSS"),"yyyy")

    DateUtils.format(DateUtils.parseDate(row[2],"yyyy-MM-dd HH:mm:ss.SSS"),"yyyyMM")

    DateUtils.format(DateUtils.parseDate(row[2],"yyyy-MM-dd HH:mm:ss.SSS"),"yyyyMMdd")

    Figure 9 Configuring the expression

    The expressions in CDM support field conversion of common character strings, dates, and values.

  4. Click Next and set task parameters. Generally, retain the default values of all parameters.

    In this step, you can configure the following optional functions:
    • Retry Upon Failure: If the job fails to be executed, you can determine whether to automatically retry. Retain the default value Never.
    • Group: Select the group to which the job belongs. The default group is DEFAULT. On the Job Management page, jobs can be displayed, started, or exported by group.
    • Schedule Execution: To configure scheduled jobs, see Scheduling Job Execution. Retain the default value No.
    • Concurrent Extractors: Enter the number of extractors to be concurrently executed. Retain the default value 1.
    • Write Dirty Data: Specify this parameter if data that fails to be processed or filtered out during job execution needs to be written to OBS for future viewing. Before writing dirty data, create an OBS link. Retain the default value No so that dirty data is not recorded.
    • Delete Job After Completion: Retain the default value Do not delete.

  5. Click Save and Run. The Job Management page is displayed, on which you can view the job execution progress and result.
  6. After the job is successfully executed, in the Operation column of the job, click Historical Record to view the job's historical execution records and read/write statistics.

    On the Historical Record page, click Log to view the job logs.