PostgreSQL 扩展的 JDBC API

PostgreSQL 是一个可扩展的数据库系统。您可以将自己的函数添加到服务器，然后可以从查询中调用这些函数，甚至可以添加自己的数据类型。由于这些是 PostgreSQL 独有的功能，因此我们从 Java 支持它们，并带有一组扩展 API。标准驱动程序核心中的某些功能实际上使用这些扩展来实现大型对象等。

要访问某些扩展，您需要使用一些在org.postgresql.PGConnection类中的额外方法。在这种情况下，您需要强制转换Driver.getConnection()的返回值。例如：

Connection db = Driver.getConnection(url, username, password);
// ...
// later on
Fastpath fp = db.unwrap(org.postgresql.PGConnection.class).getFastpathAPI();

PostgreSQL有一组数据类型，可以将几何特征存储到表中。其中包括单点、线和面。我们在 Java 中使用org.postgresql.geometric包支持这些类型。有关可用的类和特性的详细信息，请参阅 延伸阅读 中提到的 Javadoc。

例 9.1.在 JDBC 中使用 CIRCLE 数据类型

import java.sql.*;

import org.postgresql.geometric.PGpoint;
import org.postgresql.geometric.PGcircle;

public class GeometricTest {
    public static void main(String args[]) throws Exception {
        String url = "jdbc:postgresql://localhost:5432/test";
        try (Connection conn = DriverManager.getConnection(url, "test", "")) {
            try (Statement stmt = conn.createStatement()) {
                stmt.execute("CREATE TEMP TABLE geomtest(mycirc circle)");
            }
            insertCircle(conn);
            retrieveCircle(conn);
        }
    }

    private static void insertCircle(Connection conn) throws SQLException {
        PGpoint center = new PGpoint(1, 2.5);
        double radius = 4;
        PGcircle circle = new PGcircle(center, radius);
        try (PreparedStatement ps = conn.prepareStatement("INSERT INTO geomtest(mycirc) VALUES (?)")) {
            ps.setObject(1, circle);
            ps.executeUpdate();
        }
    }

    private static void retrieveCircle(Connection conn) throws SQLException {
        try (Statement stmt = conn.createStatement()) {
            try (ResultSet rs = stmt.executeQuery("SELECT mycirc, area(mycirc) FROM geomtest")) {
                while (rs.next()) {
                    PGcircle circle = (PGcircle) rs.getObject(1);
                    double area = rs.getDouble(2);

                    System.out.println("Center (X, Y) = (" + circle.center.x + ", " + circle.center.y + ")");
                    System.out.println("Radius = " + circle.radius);
                    System.out.println("Area = " + area);
                }
            }
        }
    }
}

标准 JDBC 规范支持大对象。然而，那类接口有限，PostgreSQL 提供的 API 允许随机访问对象内容，就像它是本地文件一样。

org.postgresql.largeobject包为 Java 提供了对应 libpq C 接口的大对象 API。它由两个类组成，LargeObjectManager处理创建、打开和删除大对象，以及LargeObject处理与单个对象相关的操作。有关此 API 的示例用法，请参阅 存储二进制数据，例 7.1 “在 JDBC 中处理二进制数据”。

收听和通知为访问同一 PostgreSQL 数据库的进程集合提供了一种简单形式的信号或进程间通信机制。有关通知的详细信息，请参阅主服务器文档。本节仅介绍通知的 JDBC 特定方面。

标准LISTEN、NOTIFY和UNLISTEN命令通过标准Statement接口发出。要检索和处理检索到的通知，必须强制转换Connection为PostgreSQL特定的PGConnection扩展接口。从那里可以使用getNotifications()方法检索任何未完成的通知。

JDBC 驱动程序的一个关键限制是它无法接收异步通知，并且必须轮询后端以检查是否发出了任何通知。可以为轮询函数提供超时，但随后来自其他线程的语句的执行将阻塞。

例 9.2.接收通知

import java.sql.*;

public class NotificationTest {
    public static void main(String args[]) throws Exception {
        Class.forName("org.postgresql.Driver");
        String url = "jdbc:postgresql://localhost:5432/test";

        // Create two distinct connections, one for the notifier
        // and another for the listener to show the communication
        // works across connections although this example would
        // work fine with just one connection.

        Connection lConn = DriverManager.getConnection(url, "test", "");
        Connection nConn = DriverManager.getConnection(url, "test", "");

        // Create two threads, one to issue notifications and
        // the other to receive them.

        Listener listener = new Listener(lConn);
        Notifier notifier = new Notifier(nConn);
        listener.start();
        notifier.start();
    }
}

class Listener extends Thread {
    private Connection conn;
    private org.postgresql.PGConnection pgconn;

    Listener(Connection conn) throws SQLException {
        this.conn = conn;
        this.pgconn = conn.unwrap(org.postgresql.PGConnection.class);
        Statement stmt = conn.createStatement();
        stmt.execute("LISTEN mymessage");
        stmt.close();
    }

    public void run() {
        try {
            while (true) {
                org.postgresql.PGNotification notifications[] = pgconn.getNotifications();

                // If this thread is the only one that uses the connection, a timeout can be used to
                // receive notifications immediately:
                // org.postgresql.PGNotification notifications[] = pgconn.getNotifications(10000);

                if (notifications != null) {
                    for (int i = 0; i < notifications.length; i++)
                        System.out.println("Got notification: " + notifications[i].getName());
                }

                // wait a while before checking again for new
                // notifications

                Thread.sleep(500);
            }
        } catch (SQLException sqle) {
            sqle.printStackTrace();
        } catch (InterruptedException ie) {
            ie.printStackTrace();
        }
    }
}

class Notifier extends Thread {
    private Connection conn;

    public Notifier(Connection conn) {
        this.conn = conn;
    }

    public void run() {
        while (true) {
            try {
                Statement stmt = conn.createStatement();
                stmt.execute("NOTIFY mymessage");
                stmt.close();
                Thread.sleep(2000);
            } catch (SQLException sqle) {
                sqle.printStackTrace();
            } catch (InterruptedException ie) {
                ie.printStackTrace();
            }
        }
    }
}

The PostgreSQL server allows clients to compile sql statements that are expected to be reused to avoid the overhead of parsing and planning the statement for every execution. This functionality is available at the SQL level via PREPARE and EXECUTE beginning with server version 7.3, and at the protocol level beginning with server version 7.4, but as Java developers we really just want to use the standard PreparedStatement interface.

PostgreSQL 9.2 release notes: prepared statements used to be optimized once, without any knowledge of the parameters’ values. With 9.2, the planner will use specific plans regarding to the parameters sent (the query will be planned at execution), except if the query is executed several times and the planner decides that the generic plan is not too much more expensive than the specific plans.

Server side prepared statements can improve execution speed as

1. It sends just statement handle (e.g. S_1) instead of full SQL text
2. It enables use of binary transfer (e.g. binary int4, binary timestamps, etc); the parameters and results are much faster to parse
3. It enables the reuse server-side execution plan
4. The client can reuse result set column definition, so it does not have to receive and parse metadata on each execution

以前版本的驱动程序使用 PREPARE 和 EXECUTE 来实现服务端的预备语句。
从 7.3 开始的所有服务器版本都支持此功能，但在查询结果中产生了应用程序可见的变更，例如缺少结果集元数据和行更新计数。当前驱动程序使用 V3 协议级别的等效项，这样可以避免查询结果中的这些变更。扩展查询协议准备一个临时的“未命名语句”。 有关详细信息，请参阅第 53.2.3 节的扩展查询。

The driver uses the Extended Protocol by default when the PreparedStatement API is used.

An internal counter keeps track of how many times the statement has been executed and when it reaches the prepareThreshold (default 5) the driver will switch to creating a named statement and using Prepare and Execute.

It is generally a good idea to reuse the same PreparedStatement object for performance reasons, however the driver is able to server-prepare statements automatically across connection.prepareStatement(...) calls.

For instance:

PreparedStatement ps = con.prepareStatement("select /*test*/ ?::int4");
ps.setInt(1, 42);
ps.executeQuery().close();
ps.close();

PreparedStatement ps = con.prepareStatement("select /*test*/ ?::int4");
ps.setInt(1, 43);
ps.executeQuery().close();
ps.close();

is less efficient than

PreparedStatement ps = con.prepareStatement("select /*test*/ ?::int4");

ps.setInt(1, 42);
ps.executeQuery().close();

ps.setInt(1, 43);
ps.executeQuery().close();

however pgJDBC can use server side prepared statements in both cases.

The Statement object is bound to a Connection , and it is not a good idea to access the same Statement and/or Connection from multiple concurrent threads (except cancel() , close() , and alike cases). It might be safer to just close() the statement rather than trying to cache it somehow.

Server-prepared statements consume memory both on the client and the server, so pgJDBC limits the number of server-prepared statements per connection. It can be configured via preparedStatementCacheQueries (default 256 , the number of queries known to pgJDBC), and preparedStatementCacheSizeMiB (default 5 , that is the client side cache size in megabytes per connection). Only a subset of statement cache is server-prepared as some statements might fail to reach prepareThreshold .

There might be cases when you would want to disable use of server-prepared statements. For instance, if you route connections through a balancer that is incompatible with server-prepared statements, you have little choice.

You can disable usage of server side prepared statements by setting prepareThreshold=0

V3 protocol avoids sending column metadata on each execution, and BIND message specifies output column format. That creates a problem for cases like

SELECT * FROM mytable;
ALTER mytable ADD column ...;
SELECT * FROM mytable;

That results in cached plan must not change result type error, and it causes the transaction to fail.

The recommendation is:

1. Use explicit column names in the SELECT list
2. Avoid column type alters

There are explicit commands to deallocate all server side prepared statements. It would result in the following server-side error message: prepared statement name is invalid. Of course, it could defeat pgJDBC, however there are cases when you need to discard statements (e.g. after lots of DDLs)

The recommendation is:

1. Use simple DEALLOCATE ALL and/or DISCARD ALL commands, avoid nesting the commands into pl/pgsql or alike. The driver does understand top-level DEALLOCATE/DISCARD commands, and it invalidates client-side cache as well
2. Reconnect. The cache is per connection, so it would get invalidated if you reconnect

PostgreSQL allows to customize search_path , and it provides great power to the developer. With great power the following case could happen:

set search_path='app_v1';
SELECT * FROM mytable;
set search_path='app_v2';
SELECT * FROM mytable; -- Does mytable mean app_v1.mytable or app_v2.mytable here?

Server side prepared statements are linked to database object IDs, so it could fetch data from “old” app_v1.mytable table. It is hard to tell which behaviour is expected, however pgJDBC tries to track search_path changes, and it invalidates prepare cache accordingly.

The recommendation is:

1. Avoid changing search_path often, as it invalidates server side prepared statements
2. Use simple set search_path... commands, avoid nesting the commands into pl/pgsql or alike, otherwise pgJDBC won’t be able to identify search_path change

It is a pity that a single cached plan must not change result type could cause the whole transaction to fail. The driver could re-execute the statement automatically in certain cases.

1. In case the transaction has not failed (e.g. the transaction did not exist before execution of the statement that caused cached plan... error), then pgJDBC re-executes the statement automatically. This makes the application happy, and avoids unnecessary errors.
2. In case the transaction is in a failed state, there’s nothing to do but rollback it. pgJDBC does have “automatic savepoint” feature, and it could automatically rollback and retry the statement. The behaviour is controlled via autosave property (default never ). The value of conservative would auto-rollback for the errors related to invalid server-prepared statements.

autosave might result in severe performance issues for long transactions, as PostgreSQL backend is not optimized for the case of long transactions and lots of savepoints.

PostgreSQL replication connection does not allow to use server side prepared statements, so pgJDBC uses simple queries in the case where replication connection property is activated.

By default, pgJDBC uses server-prepared statements for PreparedStatement only, however you might want to activate server side prepared statements for regular Statement as well. For instance, if you execute the same statement through con.createStatement().executeQuery(...) , then you might improve performance by caching the statement. Of course, it is better to use PreparedStatements explicitly, however the driver has an option to cache simple statements as well.

You can do that by setting preferQueryMode to extendedCacheEverything.

the option is more of a diagnostinc/debugging sort, so be careful how you use it .

The database optimizes the execution plan for given parameter types. Consider the below case:

-- create table rooms (id int4, name varchar);
-- create index name__rooms on rooms(name);
PreparedStatement ps = con.prepareStatement("select id from rooms where name=?");
ps.setString(1, "42");

It works as expected, however what would happen if one uses setInt instead? ps.setInt(1, 42);

Even though the result would be identical, the first variation ( setString case) enables the database to use index name__rooms , and the latter does not. In case the database gets 42 as integer, it uses the plan like where cast(name as int4) = ?.

The plan has to be specific for the ( SQL text ; parameter types ) combination, so the driver has to invalidate server side prepared statements in case the statement is used with different parameter types.

This gets especially painful for batch operations as you don’t want to interrupt the batch by using alternating datatypes.

The most typical case is as follows (don’t ever use this in production):

PreparedStatement ps = con.prepareStatement("select id from rooms where ...");
if (param instanceof String) {
    ps.setString(1, param);
} else if (param instanceof Integer) {
    ps.setInt(1, ((Integer) param).intValue());
} else {
    // Does it really matter which type of NULL to use?
    // In fact, it does since data types specify which server-procedure to call
    ps.setNull(1, Types.INTEGER);
}

As you might guess, setString vs setNull(..., Types.INTEGER) result in alternating datatypes, and it forces the driver to invalidate and re-prepare server side statement.

Recommendation is to use the consistent datatype for each bind placeholder, and use the same type for setNull . Check out org.postgresql.test.jdbc2.PreparedStatementTest.testAlternatingBindType example for more details.

In case you run into cached plan must not change result type or prepared statement \"S_2\" does not exist the following might be helpful to debug the case.

1. Client logging. If you add loggerLevel=TRACE&loggerFile=pgjdbc-trace.log, you would get trace of the messages send between the driver and the backend
2. You might check org.postgresql.test.jdbc2.AutoRollbackTestSuite as it verifies lots of combinations

例 9.3.使用服务端预备语句

import java.sql.*;

public class ServerSidePreparedStatement {

    public static void main(String args[]) throws Exception {
        Class.forName("org.postgresql.Driver");
        String url = "jdbc:postgresql://localhost:5432/test";
        Connection conn = DriverManager.getConnection(url, "test", "");

        PreparedStatement pstmt = conn.prepareStatement("SELECT ?");

        // cast to the pg extension interface
        org.postgresql.PGStatement pgstmt = pstmt.unwrap(org.postgresql.PGStatement.class);

        // on the third execution start using server side statements
        pgstmt.setPrepareThreshold(3);

        for (int i = 1; i <= 5; i++) {
            pstmt.setInt(1, i);
            boolean usingServerPrepare = pgstmt.isUseServerPrepare();
            ResultSet rs = pstmt.executeQuery();
            rs.next();
            System.out.println("Execution: " + i + ", Used server side: " + usingServerPrepare + ", Result: " + rs.getInt(1));
            rs.close();
        }

        pstmt.close();
        conn.close();
    }
}

Which produces the expected result of using server side prepared statements upon the third execution.

The example shown above requires the programmer to use PostgreSQL specific code in a supposedly portable API which is not ideal. Also it sets the threshold only for that particular statement which is some extra typing if we wanted to use that threshold for every statement. Let’s take a look at the other ways to set the threshold to enable server side prepared statements. There is already a hierarchy in place above a PreparedStatement , the Connection it was created from, and above that the source of the connection be it a Datasource or a URL. The server side prepared statement threshold can be set at any of these levels such that the value will be the default for all of its children.

// pg extension interfaces
org.postgresql.PGConnection pgconn;
org.postgresql.PGStatement pgstmt;

// set a prepared statement threshold for connections created from this url
String url = "jdbc:postgresql://localhost:5432/test?prepareThreshold=3";

// see that the connection has picked up the correct threshold from the url
Connection conn = DriverManager.getConnection(url, "test", "");
pgconn = conn.unwrap(org.postgresql.PGConnection.class);
System.out.println(pgconn.getPrepareThreshold()); // Should be 3

// see that the statement has picked up the correct threshold from the connection
PreparedStatement pstmt = conn.prepareStatement("SELECT ?");
pgstmt = pstmt.unwrap(org.postgresql.PGStatement.class);
System.out.println(pgstmt.getPrepareThreshold()); // Should be 3

// change the connection's threshold and ensure that new statements pick it up
pgconn.setPrepareThreshold(5);
PreparedStatement pstmt = conn.prepareStatement("SELECT ?");
pgstmt = pstmt.unwrap(org.postgresql.PGStatement.class);
System.out.println(pgstmt.getPrepareThreshold()); // Should be 5

PostgreSQL支持服务器参数，也称为服务器变量，或者在内部称为大统一配置（GUC）变量。 这些变量可由SET命令、postgresql.conf、ALTER SYSTEM SET、ALTER USER SET、ALTER DATABASE SET、可供 SQL 调用的set_config(...)函数等操作 。请参阅 PostgreSQL手册。

For a subset of these variables the server will automatically report changes to the value to the client driver and application. These variables are known internally as GUC_REPORT variables after the name of the flag that enables the functionality.

The server keeps track of all the variable scopes and reports when a variable reverts to a prior value, so the client doesn’t have to guess what the current value is and whether some server-side function could’ve changed it. Whenever the value changes, no matter why or how it changes, the server reports the new effective value in a Parameter Status protocol message to the client. pgJDBC uses many of these reports internally.

As of pgJDBC 42.2.6, it also exposes the parameter status information to user applications via the PGConnection extensions interface.

Two methods on org.postgresql.PGConnection provide the client interface to reported parameters. Parameter names are case-insensitive and case-preserving.

• Map PGConnection.getParameterStatuses() - return a map of all reported parameters and their values.

• String PGConnection.getParameterStatus() - shorthand to retrieve one value by name, or null if no value has been reported.

See the PGConnection JavaDoc for details.

If you’re working directly with a java.sql.Connection you can

import org.postgresql.PGConnection;

void my_function(Connection conn) {
    System.out.println("My application name is " + ((PGConnection) conn).getParameterStatus("application_name"));
}

The libpq equivalent is the PQparameterStatus(...) API function.

Postgres 9.4 (released in December 2014) introduced a new feature called logical replication. Logical replication allows changes from a database to be streamed in real-time to an external system. The difference between physical replication and logical replication is that logical replication sends data over in a logical format whereas physical replication sends data over in a binary format. Additionally logical replication can send over a single table, or database. Binary replication replicates the entire cluster in an all or nothing fashion; which is to say there is no way to get a specific table or database using binary replication

Prior to logical replication keeping an external system synchronized in real time was problematic. The application would have to update/invalidate the appropriate cache entries, reindex the data in your search engine, send it to your analytics system, and so on.

This suffers from race conditions and reliability problems. For example if slightly different data gets written to two different datastores (perhaps due to a bug or a race condition), the contents of the datastores will gradually drift apart — they will become more and more inconsistent over time. Recovering from such gradual data corruption is difficult.

Logical decoding takes the database’s write-ahead log (WAL), and gives us access to row-level change events: every time a row in a table is inserted, updated or deleted, that’s an event. Those events are grouped by transaction, and appear in the order in which they were committed to the database. Aborted/rolled-back transactions do not appear in the stream. Thus, if you apply the change events in the same order, you end up with an exact, transactionally consistent copy of the database. It’s looks like the Event Sourcing pattern that you previously implemented in your application, but now it’s available out of the box from the PostgreSQL database.

For access to real-time changes PostgreSQL provides the streaming replication protocol. Replication protocol can be physical or logical. Physical replication protocol is used for Master/Secondary replication. Logical replication protocol can be used to stream changes to an external system.

Since the JDBC API does not include replication PGConnection implements the PostgreSQL API

Your database should be configured to enable logical or physical replication

• Property max_wal_senders should be at least equal to the number of replication consumers
• Property wal_keep_segments should contain count wal segments that can’t be removed from database.
• Property wal_level for logical replication should be equal to logical.
• Property max_replication_slots should be greater than zero for logical replication, because logical replication can’t work without replication slot.

Enable connect user with replication privileges to replication stream.

local   replication   all                   trust
host    replication   all   127.0.0.1/32    md5
host    replication   all   ::1/128         md5

postgresql.conf

max_wal_senders = 4             # max number of walsender processes
wal_keep_segments = 4           # in logfile segments, 16MB each; 0 disables
wal_level = logical             # minimal, replica, or logical
max_replication_slots = 4       # max number of replication slots

pg_hba.conf

# Allow replication connections from localhost, by a user with the
# replication privilege.
local   replication   all                   trust
host    replication   all   127.0.0.1/32    md5
host    replication   all   ::1/128         md5

Logical replication uses a replication slot to reserve WAL logs on the server and also defines which decoding plugin to use to decode the WAL logs to the required format, for example you can decode changes as json, protobuf, etc. To demonstrate how to use the pgJDBC replication API we will use the test_decoding plugin that is included in the postgresql-contrib package, but you can use your own decoding plugin. There are a few on github which can be used as examples.

In order to use the replication API, the Connection has to be created in replication mode, in this mode the connection is not available to execute SQL commands, and can only be used with replication API. This is a restriction imposed by PostgreSQL.

例 9.4.创建复制连接

String url = "jdbc:postgresql://localhost:5432/postgres";
Properties props = new Properties();
PGProperty.USER.set(props, "postgres");
PGProperty.PASSWORD.set(props, "postgres");
PGProperty.ASSUME_MIN_SERVER_VERSION.set(props, "9.4");
PGProperty.REPLICATION.set(props, "database");
PGProperty.PREFER_QUERY_MODE.set(props, "simple");

Connection con = DriverManager.getConnection(url, props);
PGConnection replConnection = con.unwrap(PGConnection.class);

The entire replication API is grouped in org.postgresql.replication.PGReplicationConnection and is available via org.postgresql.PGConnection#getReplicationAPI .

Before you can start replication protocol, you need to have replication slot, which can be also created via pgJDBC API.

例 9.5.通过 pgJDBC API 创建复制槽

replConnection.getReplicationAPI()
    .createReplicationSlot()
    .logical()
    .withSlotName("demo_logical_slot")
    .withOutputPlugin("test_decoding")
    .make();

Once we have the replication slot, we can create a ReplicationStream.

例 9.6.创建逻辑复制流

PGReplicationStream stream =
    replConnection.getReplicationAPI()
        .replicationStream()
        .logical()
        .withSlotName("demo_logical_slot")
        .withSlotOption("include-xids", false)
        .withSlotOption("skip-empty-xacts", true)
        .start();

The replication stream will send all changes since the creation of the replication slot or from replication slot restart LSN if the slot was already used for replication. You can also start streaming changes from a particular LSN position, in that case LSN position should be specified when you create the replication stream.

例 9.7.从特定位置创建逻辑复制流

LogSequenceNumber waitLSN = LogSequenceNumber.valueOf("6F/E3C53568");

PGReplicationStream stream =
    replConnection.getReplicationAPI()
        .replicationStream()
        .logical()
        .withSlotName("demo_logical_slot")
        .withSlotOption("include-xids", false)
        .withSlotOption("skip-empty-xacts", true)
        .withStartPosition(waitLSN)
        .start();

Via withSlotOption we also can specify options that will be sent to our output plugin, this allows the user to customize decoding. For example, I have my own output plugin that has a property sensitive=true which will include changes by sensitive columns to change event.

例 9.8.设置 xids=true 的示例输出

BEGIN 105779
table public.test_logic_table: INSERT: pk[integer]:1 name[character varying]:'previous value'
COMMIT 105779

例 9.9.设置 xids=false 的示例输出

BEGIN
table public.test_logic_table: INSERT: pk[integer]:1 name[character varying]:'previous value'
COMMIT

During replication the database and consumer periodically exchange ping messages. When the database or client do not receive ping message within the configured timeout, replication has been deemed to have stopped and an exception will be thrown and the database will free resources. In PostgreSQL the ping timeout is configured by the property wal_sender_timeout (default = 60 seconds). Replication stream in pgjdc can be configured to send feedback(ping) when required or by time interval. It is recommended to send feedback(ping) to the database more often than configured wal_sender_timeout . In production systems I use value equal to wal_sender_timeout / 3 . It’s avoids a potential problems with networks and changes to be streamed without disconnects by timeout. To specify the feedback interval use withStatusInterval method.

Example 9.10. Replication stream with configured feedback interval equal to 20 sec

PGReplicationStream stream =
    replConnection.getReplicationAPI()
        .replicationStream()
        .logical()
        .withSlotName("demo_logical_slot")
        .withSlotOption("include-xids", false)
        .withSlotOption("skip-empty-xacts", true)
        .withStatusInterval(20, TimeUnit.SECONDS)
        .start();

After create PGReplicationStream , it’s time to start receive changes in real-time.

Changes can be received from stream as blocking( org.postgresql.replication.PGReplicationStream#read ) or as non-blocking (org.postgresql.replication.PGReplicationStream#readPending ). Both methods receive changes as a java.nio.ByteBuffer with the payload from the send output plugin. We can’t receive part of message, only the full message that was sent by the output plugin. ByteBuffer contains message in format that is defined by the decoding output plugin, it can be simple String, json, or whatever the plugin determines. That’s why pgJDBC returns the raw ByteBuffer instead of making assumptions.

Example 9.11. Example send message from output plugin.

OutputPluginPrepareWrite(ctx, true);
appendStringInfo(ctx->out, "BEGIN %u", txn->xid);
OutputPluginWrite(ctx, true);

Example 9.12. Receive changes via replication stream.

while (true) {
    //non blocking receive message
    ByteBuffer msg = stream.readPending();

    if (msg == null) {
        TimeUnit.MILLISECONDS.sleep(10 L);
        continue;
    }

    int offset = msg.arrayOffset();
    byte[] source = msg.array();
    int length = source.length - offset;
    System.out.println(new String(source, offset, length));
}

As mentioned previously, replication stream should periodically send feedback to the database to prevent disconnect via timeout. Feedback is automatically sent when read or readPending are called if it’s time to send feedback. Feedback can also be sent via org.postgresql.replication.PGReplicationStream#forceUpdateStatus() regardless of the timeout. Another important duty of feedback is to provide the server with the Logial Sequence Number (LSN) that has been successfully received and applied to consumer, it is necessary for monitoring and to truncate/archive WAL’s that that are no longer needed. In the event that replication has been restarted, it’s will start from last successfully processed LSN that was sent via feedback to database.

The API provides the following feedback mechanism to indicate the successfully applied LSN by the current consumer. LSN’s before this can be truncated or archived. org.postgresql.replication.PGReplicationStream#setFlushedLSN and org.postgresql.replication.PGReplicationStream#setAppliedLSN . You always can get last receive LSN via org.postgresql.replication.PGReplicationStream#getLastReceiveLSN .

Example 9.13. Add feedback indicating a successfully process LSN

while (true) {
    //Receive last successfully send to queue message. LSN ordered.
    LogSequenceNumber successfullySendToQueue = getQueueFeedback();
    if (successfullySendToQueue != null) {
        stream.setAppliedLSN(successfullySendToQueue);
        stream.setFlushedLSN(successfullySendToQueue);
    }

    //non blocking receive message
    ByteBuffer msg = stream.readPending();

    if (msg == null) {
        TimeUnit.MILLISECONDS.sleep(10 L);
        continue;
    }

    asyncSendToQueue(msg, stream.getLastReceiveLSN());
}

Example 9.14. Full example of logical replication

String url = "jdbc:postgresql://localhost:5432/test";
Properties props = new Properties();
PGProperty.USER.set(props, "postgres");
PGProperty.PASSWORD.set(props, "postgres");
PGProperty.ASSUME_MIN_SERVER_VERSION.set(props, "9.4");
PGProperty.REPLICATION.set(props, "database");
PGProperty.PREFER_QUERY_MODE.set(props, "simple");

Connection con = DriverManager.getConnection(url, props);
PGConnection replConnection = con.unwrap(PGConnection.class);

replConnection.getReplicationAPI()
    .createReplicationSlot()
    .logical()
    .withSlotName("demo_logical_slot")
    .withOutputPlugin("test_decoding")
    .make();

//some changes after create replication slot to demonstrate receive it
sqlConnection.setAutoCommit(true);
Statement st = sqlConnection.createStatement();
st.execute("insert into test_logic_table(name) values('first tx changes')");
st.close();

st = sqlConnection.createStatement();
st.execute("update test_logic_table set name = 'second tx change' where pk = 1");
st.close();

st = sqlConnection.createStatement();
st.execute("delete from test_logic_table where pk = 1");
st.close();

PGReplicationStream stream =
    replConnection.getReplicationAPI()
    .replicationStream()
    .logical()
    .withSlotName("demo_logical_slot")
    .withSlotOption("include-xids", false)
    .withSlotOption("skip-empty-xacts", true)
    .withStatusInterval(20, TimeUnit.SECONDS)
    .start();

while (true) {
    //non blocking receive message
    ByteBuffer msg = stream.readPending();

    if (msg == null) {
        TimeUnit.MILLISECONDS.sleep(10 L);
        continue;
    }

    int offset = msg.arrayOffset();
    byte[] source = msg.array();
    int length = source.length - offset;
    System.out.println(new String(source, offset, length));

    //feedback
    stream.setAppliedLSN(stream.getLastReceiveLSN());
    stream.setFlushedLSN(stream.getLastReceiveLSN());
}

Where output looks like this, where each line is a separate message.

BEGIN
table public.test_logic_table: INSERT: pk[integer]:1 name[character varying]:'first tx changes'
COMMIT
BEGIN
table public.test_logic_table: UPDATE: pk[integer]:1 name[character varying]:'second tx change'
COMMIT
BEGIN
table public.test_logic_table: DELETE: pk[integer]:1
COMMIT

API for physical replication looks like the API for logical replication. Physical replication does not require a replication slot. And ByteBuffer will contain the binary form of WAL logs. The binary WAL format is a very low level API, and can change from version to version. That is why replication between different major PostgreSQL versions is not possible. But physical replication can contain many important data, that is not available via logical replication. That is why pgJDBC contains an implementation for both.

例 9.15.使用物理复制

LogSequenceNumber lsn = getCurrentLSN();

Statement st = sqlConnection.createStatement();
st.execute("insert into test_physic_table(name) values('previous value')");
st.close();

PGReplicationStream stream =
    pgConnection
    .getReplicationAPI()
    .replicationStream()
    .physical()
    .withStartPosition(lsn)
    .start();

ByteBuffer read = stream.read();

PostgreSQL provides robust support for array data types as column types, function arguments and criteria in where clauses. There are several ways to create arrays with pgJDBC.

java.sql.Connection.createArrayOf(String, Object[]) 可用于从Object[]实例创建 java.sql.Array（注意：这包括基元数组和对象多维数组）。 类似的方法org.postgresql.PGConnection.createArrayOf(String, Object)提供对基元数组类型的支持。从这些方法返回的java.sql.Array对象可以在其他方法中使用，例如 PreparedStatement.setArray(int, Array)。

The following types of arrays support binary representation in requests and can be used in PreparedStatement.setObject