PostgreSQL Reader - - Alibaba Cloud Documentation Center

Background information

PostgreSQL Reader reads data from PostgreSQL.

PostgreSQL Reader connects to a remote PostgreSQL database by using Java Database Connectivity (JDBC), generates an SQL statement based on your configurations, and then sends the statement to the database. The system executes the statement on the database and returns data. Then, PostgreSQL Reader assembles the returned data into abstract datasets of the data types supported by Data Integration and sends the datasets to a writer.

PostgreSQL Reader generates the SQL statement based on the settings of the table, column, and where parameters and sends the generated statement to the PostgreSQL database.
If you specify the querySql parameter, PostgreSQL Reader directly sends the value of this parameter to the PostgreSQL database.

Precautions

If the name of a PostgreSQL table or a field in the table starts with a digit or contains letters or hyphens (-), you must use double quotation marks (") to escape the name. Otherwise, PostgreSQL Reader fails to read data from the PostgreSQL database. For PostgreSQL Reader, double quotation marks (") are keywords in JSON code. Therefore, you must use backslashes (\) to escape the double quotation marks ("). For example, if the name of a PostgreSQL table is 123Test, the name becomes \"123Test\" after it is escaped.

Note

Each double quotation mark (") must be escaped by using a backslash (\).
You can use only the code editor to escape characters.

The following code provides an example on how to use the code editor to escape characters:

"parameter": {
    "datasource": "abc",
    "column": [
        "id",
        "\"123Test\"", // Add escape characters.
],
"where": "",
"splitPk": "id",
"table": "public.wpw_test"
},

Data types

PostgreSQL Reader supports most PostgreSQL data types. Make sure that the data types of your database are supported.

The following table lists the data types that are supported by PostgreSQL Reader.


Category	PostgreSQL data type
Integer	BIGINT, BIGSERIAL, INTEGER, SMALLINT, and SERIAL
Floating point	DOUBLE, PRECISION, MONEY, NUMERIC, and REAL
String	VARCHAR, CHAR, TEXT, BIT, and INET
Date and time	DATE, TIME, and TIMESTAMP
Boolean	BOOLEAN
Binary	BYTEA

Note

PostgreSQL Reader supports only the data types that are listed in the preceding table.
You can convert the MONEY, INET, and BIT data types by using syntax such as a_inet::varchar.

Parameters


Parameter	Description	Required	Default value
datasource	The name of the data source. It must be the same as the name of the added data source. You can add data sources by using the code editor.	Yes	No default value
table	The name of the table from which you want to read data.	Yes	No default value
column	The names of the columns from which you want to read data. Specify the names in a JSON array. The default value is [ * ], which indicates all the columns in the source table. You can select specific columns to read. The column order can be changed. This indicates that you can specify columns in an order different from the order specified by the schema of the source table. Constants are supported. The column names must be arranged in compliance with the SQL syntax that is supported by PostgreSQL, such as `["id", "table","1", "'mingya.wmy'", "'null'", "to_char(a+1)", "2.3" , "true"]`. id: a column name. table: the name of a column that contains reserved keywords. 1: an integer constant. 'mingya.wmy': a string constant, which is enclosed in single quotation marks ('). 'null': a string. to_char(a+1): a function expression that is used to calculate the length of a string. 2.3: a floating-point constant. true: a Boolean value. The column parameter must explicitly specify all the columns from which you want to read data. The parameter cannot be left empty.	Yes	No default value
splitPk	The field that is used for data sharding when PostgreSQL Reader reads data. If you specify this parameter, the source table is sharded based on the value of this parameter. Data Integration then runs parallel threads to read data. This way, data can be synchronized more efficiently. We recommend that you set the splitPk parameter to the name of the primary key column of the table. Data can be evenly distributed to different shards based on the primary key column, but not intensively distributed only to specific shards. The splitPk parameter supports sharding for data only of integer data types. If you set this parameter to a column of an unsupported data type, such as a string, floating point, or date data type, PostgreSQL Reader ignores the setting of the splitPk parameter and uses a single thread to read data. If the splitPk parameter is not provided or is left empty, PostgreSQL Reader uses a single thread to read data.	No	No default value
where	The WHERE clause. PostgreSQL Reader generates an SQL statement based on the settings of the table, column, and where parameters and uses the generated statement to read data. For example, you can set this parameter to `id>2 and sex=1` in an actual business scenario to synchronize the data that is generated on the current day. You can use the WHERE clause to read incremental data. If the where parameter is not provided or is left empty, PostgreSQL Reader reads all data.	No	No default value
querySql (advanced parameter, which is available only in the code editor)	The SQL statement that is used for refined data filtering. If you specify this parameter, Data Integration filters data based on the value of this parameter. For example, if you want to join multiple tables for data synchronization, set this parameter to `select a,b from table_a join table_b on table_a.id = table_b.id`. If you specify this parameter, PostgreSQL Reader ignores the settings of the table, column, and where parameters.	No	No default value
fetchSize	The number of data records to read at a time. This parameter determines the number of interactions between Data Integration and the database and affects read efficiency. Note If you set this parameter to a value greater than 2048, an out of memory (OOM) error may occur during data synchronization.	No	512

Configure PostgreSQL Reader by using the codeless UI

Configure data sources.

Configure Source and Target for the synchronization node. Configure data sources


Parameter	Description
Connection	The name of the data source from which you want to read data. This parameter is equivalent to the datasource parameter that is described in the preceding section.
Table	The name of the table from which you want to read data. This parameter is equivalent to the table parameter that is described in the preceding section.
Filter	The condition used to filter the data that you want to read. Filtering based on the LIMIT keyword is not supported. The SQL syntax is determined by the selected data source.
Shard Key	The shard key. You can use a column in the source table as the shard key. We recommend that you use the primary key column or an indexed column. Only integer columns are supported. If you specify this parameter, data sharding is performed based on the value of this parameter, and parallel threads can be used to read data. This improves data synchronization efficiency. Note The Shard Key parameter is displayed only after you select the data source for the synchronization node.

Configure field mappings. This operation is equivalent to setting the column parameter that is described in the preceding section.

Fields in the source on the left have a one-to-one mapping with fields in the destination on the right. You can click Add to add a field. To remove an added field, move the pointer over the field and click the Remove icon. Field mappings


Operation	Description
Map Fields with the Same Name	Click Map Fields with the Same Name to establish mappings between fields with the same name. The data types of the fields must match.
Map Fields in the Same Line	Click Map Fields in the Same Line to establish mappings between fields in the same row. The data types of the fields must match.
Delete All Mappings	Click Delete All Mappings to remove the mappings that are established.
Auto Layout	Click Auto Layout. Then, the system automatically sorts the fields based on specific rules.
Change Fields	You can manually edit fields in the source table. Each field occupies a row. The first and the last blank rows are included, whereas other blank rows are ignored.
Add	Click Add to add a field. Take note of the following rules when you add a field: You can enter constants. Each constant must be enclosed in single quotation marks ('), such as 'abc' and '123'. You can use scheduling parameters, such as ${bizdate}. You can enter functions that are supported by relational databases, such as now() and count(1). If the field that you entered cannot be parsed, the value of Type for the field is Unidentified.

Configure channel control policies.


Parameter	Description
Expected Maximum Concurrency	The maximum number of parallel threads that the synchronization node uses to read data from the source or write data to the destination. You can configure the parallelism for the synchronization node on the codeless UI.
Bandwidth Throttling	Specifies whether to enable bandwidth throttling. You can enable bandwidth throttling and specify a maximum transmission rate to prevent heavy read workloads on the source. We recommend that you enable bandwidth throttling and set the maximum transmission rate to an appropriate value based on the configurations of the source.
Dirty Data Records Allowed	The maximum number of dirty data records allowed.
Distributed Execution	The distributed execution mode that allows you to split your node into pieces and distribute them to multiple Elastic Compute Service (ECS) instances for parallel execution. This speeds up synchronization. If you use a large number of parallel threads to run your synchronization node in distributed execution mode, excessive access requests are sent to the data sources. Therefore, before you use the distributed execution mode, you must evaluate the access load on the data sources. You can enable this mode only if you use an exclusive resource group for Data Integration. For more information about exclusive resource groups for Data Integration, see Exclusive resource groups for Data Integration and Create and use an exclusive resource group for Data Integration.

Configure PostgreSQL Reader by using the code editor

In the following code, a synchronization node is configured to read data from a PostgreSQL database. For more information about how to configure a synchronization node by using the code editor, see Create a sync node by using the code editor.

{
    "type":"job",
    "version":"2.0",// The version number. 
    "steps":[
        {
            "stepType":"postgresql",// The reader type. 
            "parameter":{
                "datasource":"",// The name of the data source. 
                "column":[// The names of the columns from which you want to read data. 
                    "col1",
                    "col2"
                ],
                "where":"",// The WHERE clause. 
                "splitPk":"",// The shard key based on which the table is sharded. Data Integration runs parallel threads to synchronize data. 
                "table":""// The name of the source table. 
            },
            "name":"Reader",
            "category":"reader"
        },
        { 
            "stepType":"stream",
            "parameter":{},
            "name":"Writer",
            "category":"writer"
        }
    ],
    "setting":{
        "errorLimit":{
            "record":"0"// The maximum number of dirty data records allowed. 
        },
        "speed":{
            "throttle":false, // Specifies whether to enable bandwidth throttling. The value false indicates that bandwidth throttling is disabled, and the value true indicates that bandwidth throttling is enabled. The mbps parameter takes effect only when the throttle parameter is set to true. 
            "concurrent":1, // The maximum number of parallel threads. 
            "mbps":"12"// The maximum transmission rate.
        }
    },
    "order":{
        "hops":[
            {
                "from":"Reader",
                "to":"Writer"
            }
        ]
    }
}

Additional information

Data synchronization between primary and secondary databases
A secondary PostgreSQL database can be deployed for disaster recovery. The secondary database continuously synchronizes data from the primary database based on binary logs. Data latency between the primary and secondary databases cannot be prevented. This may result in data inconsistency.
Data consistency control
PostgreSQL is a relational database management system (RDBMS) that supports strong consistency for data queries. A database snapshot is created before a synchronization node starts. PostgreSQL Reader reads data from the database snapshot. Therefore, if new data is written to the database during data synchronization, PostgreSQL Reader cannot obtain the new data.

Data consistency cannot be ensured if you enable PostgreSQL Reader to use parallel threads to read data in a synchronization node.

PostgreSQL Reader shards the source table based on the value of the splitPk parameter and uses parallel threads to read data. These parallel threads belong to different transactions. They read data at different points in time. Therefore, the parallel threads observe different snapshots.

Data inconsistencies cannot be prevented if parallel threads are used for a synchronization node. The following workarounds can be used:
- Enable PostgreSQL Reader to use a single thread to read data in a synchronization node. This indicates that you do not need to specify a shard key for PostgreSQL Reader. This way, data consistency is ensured, but data is synchronized at low efficiency.
- Make sure that no data is written to the source table during data synchronization. This ensures that the data in the source table remains unchanged during data synchronization. For example, you can lock the source table or disable data synchronization between primary and secondary databases. This way, data is efficiently synchronized, but your ongoing services may be interrupted.
Character encoding
A PostgreSQL database supports only the EUC_CN and UTF-8 encoding formats for simplified Chinese characters. PostgreSQL Reader uses JDBC to read data. This enables PostgreSQL Reader to automatically convert the encoding formats of characters. Therefore, you do not need to specify the encoding format.

If you specify the encoding format for a PostgreSQL database but data is written to the PostgreSQL database in a different encoding format, PostgreSQL Reader cannot identify this inconsistency and may export garbled characters.
Incremental data synchronization
PostgreSQL Reader uses JDBC to connect to a database and uses a SELECT statement with a WHERE clause to read incremental data.
- For batch data, incremental add, update, and delete operations (including logically delete operations) are distinguished by timestamps. Specify the WHERE clause based on a specific timestamp. The time indicated by the timestamp must be later than the time indicated by the latest timestamp in the previous synchronization.
- For streaming data, specify the WHERE clause based on the ID of a specific record. The ID must be greater than the maximum ID involved in the previous synchronization.
If the data that is added or modified cannot be distinguished, PostgreSQL Reader can read only full data.
Syntax validation
PostgreSQL Reader allows you to configure custom SELECT statements by using the querySql parameter but does not verify the syntax of these statements.