我有两个优势。 例如,“pple”和“纽顿”。 我分别用 g子压缩,并加入由此产生的红灯,在档案中储存。 然后,我检索档案中的内容。 当我一心一意孤行时,我会得出确切的结果。 但是,我想找到每个设想的长处。 这样做是可能的。
这是因为我储存大量数据。 i 利用缓冲规模进行检索。 当我直接试图揭穿时,我就接受了EOFException。 如果我能够获得《平等就业机会法》,我可以run开不想要的那部分,然后解冻所需内容。
我有两个优势。 例如,“pple”和“纽顿”。 我分别用 g子压缩,并加入由此产生的红灯,在档案中储存。 然后,我检索档案中的内容。 当我一心一意孤行时,我会得出确切的结果。 但是,我想找到每个设想的长处。 这样做是可能的。
这是因为我储存大量数据。 i 利用缓冲规模进行检索。 当我直接试图揭穿时,我就接受了EOFException。 如果我能够获得《平等就业机会法》,我可以run开不想要的那部分,然后解冻所需内容。
在加入两条指示之前使用任何限定性,例如空间或 com,以便你能够承认每一条指示的终结。
当你把整个扼杀在一起时,你将像这一“pple,纽顿”一样取得成果。
Now use split() method of String class to get the individual strings.
String[] strings = totalString.split("," , 0);
你可以把“pple”、“纽顿”作为两个单独的“强硬物储存,另一个物体将这两条分开。 当你读物时,你可以比较哪类物体。 这样,你就能够轻易发现分离物体。
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