我一直在寻找这个问题的答案。
在我看来,如果不引入对HDFS和Hadoop的依赖,就无法在Java程序中嵌入、读写Parquet格式。这是正确的吗?
我想在Hadoop集群之外的客户机上进行读写。
我开始对Apache Drill感到兴奋,但它似乎必须作为一个单独的进程运行。我需要的是一个进程内的能力,以读取和写入文件使用的拼图格式。
发布于 2017-02-14 18:53:58
您可以在hadoop集群外部使用java parquet客户端API编写Parquet格式。
这是一个用java编写的示例代码,它将parquet格式写入本地磁盘。
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.apache.hadoop.fs.Path;
import org.apache.parquet.avro.AvroSchemaConverter;
import org.apache.parquet.avro.AvroWriteSupport;
import org.apache.parquet.hadoop.ParquetWriter;
import org.apache.parquet.hadoop.metadata.CompressionCodecName;
import org.apache.parquet.schema.MessageType;
public class Test {
void test() throws IOException {
final String schemaLocation = "/tmp/avro_format.json";
final Schema avroSchema = new Schema.Parser().parse(new File(schemaLocation));
final MessageType parquetSchema = new AvroSchemaConverter().convert(avroSchema);
final WriteSupport<Pojo> writeSupport = new AvroWriteSupport(parquetSchema, avroSchema);
final String parquetFile = "/tmp/parquet/data.parquet";
final Path path = new Path(parquetFile);
ParquetWriter<GenericRecord> parquetWriter = new ParquetWriter(path, writeSupport, CompressionCodecName.SNAPPY, BLOCK_SIZE, PAGE_SIZE);
final GenericRecord record = new GenericData.Record(avroSchema);
record.put("id", 1);
record.put("age", 10);
record.put("name", "ABC");
record.put("place", "BCD");
parquetWriter.write(record);
parquetWriter.close();
}
}
avro_format.json,
{
"type":"record",
"name":"Pojo",
"namespace":"com.xx.test",
"fields":[
{
"name":"id",
"type":[
"int",
"null"
]
},
{
"name":"age",
"type":[
"int",
"null"
]
},
{
"name":"name",
"type":[
"string",
"null"
]
},
{
"name":"place",
"type":[
"string",
"null"
]
}
]
}
希望这能有所帮助。
https://stackoverflow.com/questions/42078757
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