This topic describes the data types and parameters that PostgreSQL Reader supports and how to configure it by using the codeless user interface (UI) and code editor.

Background information

PostgreSQL Reader connects to a remote PostgreSQL database and executes a SELECT statement to select and read data from the database. ApsaraDB RDS provides the PostgreSQL storage engine.

Specifically, PostgreSQL Reader connects to a remote PostgreSQL database by using Java Database Connectivity (JDBC), generates a SELECT statement based on your configurations, and then sends the statement to the database. The PostgreSQL database executes the statement and returns the results. Then, PostgreSQL Reader assembles the returned data to abstract datasets of custom data types that are supported by Data Integration, and passes the datasets to a writer.
  • PostgreSQL Reader generates the SELECT statement based on the table, column, and where parameters that you specify, and sends the generated SELECT statement to the PostgreSQL database.
  • If you specify the querySql parameter, PostgreSQL Reader directly sends the value of this parameter to the PostgreSQL database.
Column names in PostgreSQL may contain uppercase and lowercase letters. If a column name contains uppercase letters, Data Integration automatically converts the uppercase letters to lowercase letters by default. As a result, the column fails to be read. To resolve this issue, you must add escape characters to the column name in the code editor. The codeless UI does not allow you to add escape characters.
"parameter": {
    "datasource": "abc",
    "column": [
        "id",
        "\"pgCreateTime\"", // Add escape characters to a column name.
        "\"pgCreateTimeDay\""
],
"where": "",
"splitPk": "id",
"table": "public.wpw_test"
},

Data types

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

The following table describes the data types that PostgreSQL Reader supports.
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 BOOL
Binary BYTEA
Note
  • PostgreSQL Reader supports only the data types that are described in the preceding table.
  • You can convert the MONEY, INET, and BIT types by using syntax such as a_inet::varchar.

Parameters

Parameter Description Required Default value
datasource The connection name. It must be the same as the name of the created connection. You can create connections in the code editor. Yes N/A
table The name of the source table. Yes N/A
column The columns to be synchronized from the source table. The columns are described in a JSON array. The default value is [*], which indicates all columns in the source table.
  • Column pruning is supported. You can select specific columns to export.
  • The column order can be changed. You can configure PostgreSQL Reader to export the specified columns in an order different from that specified in the schema of the table.
  • Constants are supported. The column names must be arranged in compliance with the SQL syntax that is supported by PostgreSQL, for example, ["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.
    • 2.3: a floating-point constant.
    • true: a Boolean value.
  • The column parameter must explicitly specify a set of columns to be synchronized. The parameter cannot be left empty.
Yes N/A
splitPk The field that is used for data sharding when PostgreSQL Reader reads data. If you specify the splitPk parameter, the table is sharded based on the shard key that is specified by this parameter. Data Integration then runs concurrent threads to synchronize data. This way, data can be synchronized more efficiently.
  • We recommend that you set the splitPk parameter to the primary key of the table. Based on the primary key, data can be well distributed to different shards, but not intensively distributed to specific shards.
  • The splitPk parameter supports data sharding only for integers but not for other data types such as string, floating point, and date. If you set this parameter to a column of an unsupported type, PostgreSQL Reader ignores the splitPk parameter and reads data by using a single thread.
  • If you do not specify the splitPk parameter or leave it empty, Data Integration synchronizes data by using a single thread.
No N/A
where The WHERE clause. PostgreSQL Reader generates a SELECT statement based on the table, column, and where parameters that you specify, and uses the generated SELECT statement to select and read data. For example, set this parameter to id>2 and sex=1.
  • You can use the WHERE clause to read incremental data.
  • If you do not specify the where parameter or leave it empty, all data is read.
No N/A
querySql (available only in the code editor) The SELECT statement that is used for refined data filtering. If you specify this parameter, Data Integration filters data based on 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 the querySql parameter, PostgreSQL Reader ignores the table, column, where, and splitPk parameters that you specify. No N/A
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 reading efficiency.
Note A value greater than 2048 may lead to out of memory (OOM) during the data synchronization process.
No 512

Configure PostgreSQL Reader by using the codeless UI

  1. Configure the connections.
    Configure the connections to the source and destination data stores for the sync node.Connections section
    Parameter Description
    Connection The datasource parameter in the preceding parameter description. Select a connection type and select the name of a connection that you have configured in DataWorks.
    Table The table parameter in the preceding parameter description.
    Filter The condition for filtering the data to be synchronized. PostgreSQL Reader cannot filter data based on the limit keyword. The SQL syntax is determined by the selected connection.
    Shard Key The shard key. You can specify a column in the source table as the shard key. We recommend that you use the primary key or an indexed column as the shard key. Only integer fields are supported.
    If data sharding is performed based on the configured shard key, data can be read concurrently. This way, data can be synchronized more efficiently.
    Note The Shard Key parameter is displayed only after you select the connection to the source data store for the sync node.
  2. Configure field mapping. It is equivalent to setting the column parameter in the preceding parameter description.
    Fields in the source table on the left have a one-to-one mapping with fields in the destination table on the right. You can click Add to add a field. To remove a field, move the pointer over the field and click the Remove icon.Mappings section
    GUI element Description
    Map Fields with the Same Name Click Map Fields with the Same Name to establish a mapping 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 a mapping between fields in the same row. The data types of the fields must match.
    Delete All Mappings Click Delete All Mappings to remove mappings that have been established.
    Auto Layout Click Auto Layout to sort the fields based on specified rules.
    Change Fields Click the Change Fields icon. In the Change Fields dialog box, you can manually edit the 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 (' '), for example, 'abc' and '123'.
    • You can use scheduling parameters such as ${bizdate}.
    • You can enter functions that are supported by relational databases, for example, now() and count(1).
    • Fields that cannot be parsed are indicated by Unidentified.
  3. Configure channel control policies.Channel section
    Parameter Description
    Expected Maximum Concurrency The maximum number of concurrent threads that the sync node uses to read data from or write data to data stores. You can configure the concurrency for the node on the codeless UI.
    Bandwidth Throttling Specifies whether to enable bandwidth throttling. You can enable bandwidth throttling and set a maximum transmission rate to avoid heavy read workload of the source. We recommend that you enable bandwidth throttling and set the maximum transmission rate to a proper value.
    Dirty Data Records Allowed The maximum number of dirty data records allowed.

Configure PostgreSQL Reader by using the code editor

The following example shows how to configure a sync node to read data from a PostgreSQL database. For more information, 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 connection name.
                "column":[// The columns to be synchronized from the source table.
                    "col1",
                    "col2"
                ],
                "where":"",// The WHERE clause.
                "splitPk":"", // The shard key based on which the table is sharded. Data Integration runs concurrent threads to synchronize data based on the shard key.
                "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. A value of false indicates that the bandwidth is not throttled. A value of true indicates that the bandwidth is throttled. The maximum transmission rate takes effect only if you set this parameter to true.
            "concurrent":1 // The maximum number of concurrent threads.
        }
    },
    "order":{
        "hops":[
            {
                "from":"Reader",
                "to":"Writer"
            }
        ]
    }
}

Usage notes

  • 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 binlogs. Especially when network conditions are unfavorable, data latency between the primary and secondary databases is unavoidable, which can lead to data inconsistency.

  • Concurrency control

    PostgreSQL is a relational database management system (RDBMS), which supports strong consistency for data queries. A database snapshot is created before a sync node starts. PostgreSQL Reader reads data from the database snapshot. Therefore, if new data is written to the database during data synchronization, the reader cannot obtain the new data.

    Data consistency cannot be ensured when you enable PostgreSQL Reader to run concurrent threads in a single sync node.

    PostgreSQL Reader shards the table based on the splitPk parameter and runs multiple concurrent threads to synchronize data. These concurrent threads belong to different transactions. They read data at different time points. This means that the concurrent threads observe different snapshots.

    Theoretically, the data inconsistency issue is unavoidable if a single sync node includes multiple threads. However, two workarounds can be used:

    • Do not enable concurrent threads in a single sync node. Essentially, do not specify the splitPk parameter. This way, data consistency is ensured although data is synchronized at a low efficiency.
    • Disable writers to make sure that the data remains unchanged during data synchronization. For example, lock the table and 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, which can automatically convert the encoding of characters. Therefore, you do not need to specify the encoding format.

    If you specify an encoding format for a PostgreSQL database but data is written to the PostgreSQL database in a different encoding format, PostgreSQL Reader cannot recognize this inconsistency. As a result, garbled characters may be exported.

  • Incremental data synchronization
    PostgreSQL Reader connects to a database by using JDBC and uses a SELECT statement with a WHERE clause to read incremental data.
    • For data in batches, incremental add, update, and delete operations are distinguished by timestamps. The delete operations include logical delete operations. Specify the WHERE clause based on the timestamp. The timestamp must be later than the latest timestamp in the last synchronization.
    • For streaming data, specify the WHERE clause based on the data record ID. The data record ID must be greater than the maximum ID in the last synchronization.

    If incremental data cannot be distinguished, PostgreSQL Reader can perform only full synchronization but not incremental synchronization.

  • Syntax validation

    PostgreSQL Reader allows you to specify custom SELECT statements by using the querySql parameter but does not verify the syntax of the custom SELECT statements.