Java is one of the most popular programming languages in today's software development, but the adoption of Java in some areas like high performance computing, gaming, and media processing is not as universal as in general-purpose computing. A major drawback preventing it from being extensively adopted in those areas is its lower performance than the traditional or domain-specific languages. This paper describes two approaches to improve Java's usability in those areas by introducing vector processing capability to Java. The first approach is to provide a Java vectorization interface (JVI) that developers can program with, to explicitly expose the programs' data parallelism. The other approach is to use automatic vectorization to generate vector instructions for Java programs. It does not require programmers to modify the original source code. We evaluate the two vectorization approaches with SPECjvm2008 benchmark. The performances of scimark.fft and scimark.lu are improved up to 55% and 107% respectively when running in single thread. We also investigate some factors that impact the vectorization effects, including the memory bus bandwidth and the superscalar micro-architecture.