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我正在使用 Chronicle-queue (5.16.13) 将 json 值写入和读取历史记录文件。为了编写对象,我在循环中使用以下内容
try (final DocumentContext dc = appender.writingDocument()) {
dc.wire().write(() -> "msg").text("Hallo asdf");
System.out.println("your data was store to index="+ dc.index());
return true;
} catch (Exception e) {
logger.warn("Unable to store value to chronicle", e);
return false;
}
为了读取项目,我在循环中执行以下调用
DocumentContext documentContext;
do {
documentContext = tailer.readingDocument();
currentOffset = documentContext.index();
System.out.println("Current offset: " + currentOffset);
} while (!documentContext.isData());
我观察到变量currentOffset
没有改变,并且在一段时间后(似乎取决于有效负载大小)循环变得无限并且当前偏移量具有疯狂的值。第一个循环的输出(缩短)为
Writing 0
your data was store to index=76385993359360
Writing 1
your data was store to index=76385993359361
Writing 2
your data was store to index=76385993359362
Writing 3
your data was store to index=76385993359363
Writing 4
your data was store to index=76385993359364
Writing 5
your data was store to index=76385993359365
Writing 6
your data was store to index=76385993359366
Writing 7
your data was store to index=76385993359367
Writing 8
your data was store to index=76385993359368
Writing 9
your data was store to index=76385993359369
Writing 10
your data was store to index=76385993359370
Writing 11
your data was store to index=76385993359371
Writing 12
your data was store to index=76385993359372
Writing 13
your data was store to index=76385993359373
Writing 14
your data was store to index=76385993359374
Writing 15
your data was store to index=76385993359375
Writing 16
your data was store to index=76385993359376
Writing 17
your data was store to index=76385993359377
Writing 18
your data was store to index=76385993359378
Writing 19
your data was store to index=76385993359379
Writing 20
your data was store to index=76385993359380
Writing 21
your data was store to index=76385993359381
Writing 22
your data was store to index=76385993359382
Writing 23
your data was store to index=76385993359383
Writing 24
your data was store to index=76385993359384
Writing 25
your data was store to index=76385993359385
Writing 26
your data was store to index=76385993359386
对于第二个循环
Reading 0
Current offset: 76385993359360
Reading 1
Current offset: 76385993359360
Reading 2
Current offset: 76385993359360
Reading 3
Current offset: 76385993359360
Reading 4
Current offset: 76385993359360
Reading 5
Current offset: 76385993359360
Reading 6
Current offset: 76385993359360
Reading 7
Current offset: 76385993359360
Reading 8
Current offset: 76385993359360
Reading 9
Current offset: 76385993359360
Reading 10
Current offset: 76385993359360
Reading 11
Current offset: 76385993359360
Reading 12
Current offset: 76385993359360
Reading 13
Current offset: 76385993359360
Reading 14
Current offset: 76385993359360
Reading 15
Current offset: 76385993359360
Reading 16
Current offset: 76385993359360
Reading 17
Current offset: 76385993359360
Reading 18
Current offset: 76385993359360
Reading 19
Current offset: 76385993359360
Reading 20
Current offset: 76385993359360
Reading 21
Current offset: 76385993359360
Reading 22
Current offset: 76385993359360
Reading 23
Current offset: 76385993359360
Reading 24
Current offset: 76385993359360
Reading 25
Current offset: -9223372036854775808
我做错了什么吗?那么有人可以提示我正确的用法吗?
非常感谢!
以下单元测试对我来说失败了。
@Test
public void fails() throws Exception {
String basePath = System.getProperty("java.io.tmpdir");
String path = Files.createTempDirectory(Paths.get(basePath), "chronicle-")
.toAbsolutePath()
.toString();
logger.info("Using temp path '{}'", path);
SingleChronicleQueue chronicleQueue = SingleChronicleQueueBuilder
.single()
.path(path)
.build();
// Create Appender
ExcerptAppender appender = chronicleQueue.acquireAppender();
// Create Tailer
ExcerptTailer tailer = chronicleQueue.createTailer();
tailer.toStart();
int numberOfRecords = 10;
// Write
for (int i = 0; i <= numberOfRecords; i++) {
System.out.println("Writing " + i);
try (final DocumentContext dc = appender.writingDocument()) {
dc.wire().write(() -> "msg").text("Hello World!");
System.out.println("your data was store to index=" + dc.index());
} catch (Exception e) {
logger.warn("Unable to store value to chronicle", e);
}
}
// Read
for (int i = 0; i <= numberOfRecords; i++) {
System.out.println("Reading " + i);
DocumentContext documentContext = tailer.readingDocument();
long currentOffset = documentContext.index();
System.out.println("Current offset: " + currentOffset);
Wire wire = documentContext.wire();
if (wire != null) {
String msg = wire
.read("msg")
.text();
}
}
chronicleQueue.close();
}
输出为
Writing 0
your data was store to index=76385993359360
Writing 1
your data was store to index=76385993359361
Writing 2
your data was store to index=76385993359362
Writing 3
your data was store to index=76385993359363
Writing 4
your data was store to index=76385993359364
Writing 5
your data was store to index=76385993359365
Writing 6
your data was store to index=76385993359366
Writing 7
your data was store to index=76385993359367
Writing 8
your data was store to index=76385993359368
Writing 9
your data was store to index=76385993359369
Writing 10
your data was store to index=76385993359370
Reading 0
Current offset: 76385993359360
Reading 1
Current offset: 76385993359360
Reading 2
Current offset: 76385993359360
Reading 3
Current offset: 76385993359360
Reading 4
Current offset: -9223372036854775808
Reading 5
Current offset: -9223372036854775808
Reading 6
Current offset: -9223372036854775808
Reading 7
Current offset: -9223372036854775808
Reading 8
Current offset: -9223372036854775808
Reading 9
Current offset: -9223372036854775808
Reading 10
Current offset: -9223372036854775808
最佳答案
使用 DocumentContext 旨在成为较低级别的接口(interface)之一,并不适合每个人的口味。我赞成使用 MethodReader/MethodWriter 方法,除非您有理由在较低级别工作。
@Test
public void works() {
String path = OS.TMP + "/chronicle-" + System.nanoTime();
System.out.println("Using temp path " + path);
try (SingleChronicleQueue queue = SingleChronicleQueueBuilder
.single()
.path(path)
.build()) {
ExcerptAppender appender = queue.acquireAppender();
Messager messager = appender.methodWriter(Messager.class);
int numberOfRecords = 10;
// Write
for (int i = 0; i <= numberOfRecords; i++) {
System.out.print("Writing " + i);
messager.msg("Hello World!");
System.out.println(", your data was stored at index=" + appender.lastIndexAppended());
}
ExcerptTailer tailer = queue.createTailer();
MethodReader reader = tailer.methodReader((Messager) msg -> {
System.out.println("Current offset: " + tailer.index()
+ " msg: " + msg);
});
// Read
while (reader.readOne()) {
// busy wait.
}
}
}
这会打印
Using temp path C:\Users\peter\AppData\Local\Temp\/chronicle-412979753710181
[main] DEBUG net.openhft.chronicle.bytes.MappedFile - Allocation of 0 chunk in C:\Users\peter\AppData\Local\Temp\chronicle-412979753710181\metadata.cq4t took 15.418 ms.
[main] DEBUG net.openhft.chronicle.bytes.MappedFile - Allocation of 0 chunk in C:\Users\peter\AppData\Local\Temp\chronicle-412979753710181\20181226.cq4 took 25.061 ms.
Writing 0, your data was stored at index=76841259892736
Writing 1, your data was stored at index=76841259892737
Writing 2, your data was stored at index=76841259892738
Writing 3, your data was stored at index=76841259892739
Writing 4, your data was stored at index=76841259892740
Writing 5, your data was stored at index=76841259892741
Writing 6, your data was stored at index=76841259892742
Writing 7, your data was stored at index=76841259892743
Writing 8, your data was stored at index=76841259892744
Writing 9, your data was stored at index=76841259892745
Writing 10, your data was stored at index=76841259892746
Current offset: 76841259892736 msg: Hello World!
Current offset: 76841259892737 msg: Hello World!
Current offset: 76841259892738 msg: Hello World!
Current offset: 76841259892739 msg: Hello World!
Current offset: 76841259892740 msg: Hello World!
Current offset: 76841259892741 msg: Hello World!
Current offset: 76841259892742 msg: Hello World!
Current offset: 76841259892743 msg: Hello World!
Current offset: 76841259892744 msg: Hello World!
Current offset: 76841259892745 msg: Hello World!
Current offset: 76841259892746 msg: Hello World!
[main] DEBUG net.openhft.chronicle.queue.impl.single.SingleChronicleQueueBuilder - File released C:\Users\peter\AppData\Local\Temp\chronicle-412979753710181\20181226.cq4
[main] DEBUG net.openhft.chronicle.queue.impl.single.SingleChronicleQueueBuilder - File released C:\Users\peter\AppData\Local\Temp\chronicle-412979753710181\20181226.cq4
注意:这会写入与原始帖子相同的数据。
使用此接口(interface)方法的一个优点是,您可以完全使用带有 DTO 的方法接口(interface)来实现业务组件,而根本不使用 Chronicle(或传输)。当您从测试中删除传输时,这会简化测试业务逻辑。
关于java - Chronicle Consumer 没有正确读取记录?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/52274284/
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