我正在使用spark开发 Web 应用程序;当我要上传文件时出现问题:
public final class SparkTesting
{
public static void main(final String... args)
{
Spark.staticFileLocation("/site");
Spark.port(8080);
Spark.post("/upload", (request, response) -> {
final Part uploadedFile = request.raw().getPart("uploadedFile");
final Path path = Paths.get("/tmp/meh");
try (final InputStream in = uploadedFile.getInputStream()) {
Files.copy(in, path);
}
response.redirect("/");
return "OK";
});
}
}
但我得到这个错误:
[qtp509057984-36] ERROR spark.webserver.MatcherFilter -
java.lang.IllegalStateException: No multipart config for servlet
at org.eclipse.jetty.server.Request.getPart(Request.java:2039)
at javax.servlet.http.HttpServletRequestWrapper.getPart(HttpServletRequestWrapper.java:361)
at com.github.fge.grappa.debugger.web.SparkTesting.lambda$main$0(SparkTesting.java:20)
at com.github.fge.grappa.debugger.web.SparkTesting$$Lambda$1/920011586.handle(Unknown Source)
at spark.SparkBase$1.handle(SparkBase.java:264)
at spark.webserver.MatcherFilter.doFilter(MatcherFilter.java:154)
at spark.webserver.JettyHandler.doHandle(JettyHandler.java:60)
at org.eclipse.jetty.server.session.SessionHandler.doScope(SessionHandler.java:179)
at org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:136)
at org.eclipse.jetty.server.handler.HandlerList.handle(HandlerList.java:52)
at org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:97)
at org.eclipse.jetty.server.Server.handle(Server.java:451)
at org.eclipse.jetty.server.HttpChannel.run(HttpChannel.java:252)
at org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:266)
at org.eclipse.jetty.io.AbstractConnection$ReadCallback.run(AbstractConnection.java:240)
at org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:596)
at org.eclipse.jetty.util.thread.QueuedThreadPool$3.run(QueuedThreadPool.java:527)
at java.lang.Thread.run(Thread.java:745)
即使我尝试明确指定类型,如:
Spark.post("/upload", "multipart/form-data", etc etc)
它仍然会失败。
我可能会找到一个库来解析多部分/表单数据,获取整个内容并解析自己,但那将是一种浪费。
我可以配置 spark 来处理这种情况吗?