The data storage and reading mechanism of Apache Parquet Colmn framework in the Java class library

Apache Parquet is a column -type storage format that is used to make high -efficiency and scalable data storage and read on large -scale data sets.It uses an optimized binary encoding method to store data according to columns, thereby providing a better compression ratio and query performance. In the Java class library, Apache Parquet provides a set of API that can be used to store data to the Parquet file and read data from the ParQuet file.Below we will introduce the data storage and reading mechanism of the Apache Parquet Column framework in the Java class library, and provide some Java code examples. 1. Data storage mechanism: Apache Parquet's data storage mechanism is based on columnist storage.It encodes data according to columns, and each column is stored in different files.In the Parquet file, there are three important concepts: SCHEMA, Group (group), and Column. -SChema defines the structure of data storage, including the names, data types and coding methods of each column.You can use the `MessageType` class to define SCHEMA. -Loup is a set of data records in the Parquet file, which organizes in a way.Use the `GroupBuilder` class to create a group object and add data to it. -Column is a column in the Parquet file, which contains the data and metadata information of the column.Using the `PrimitiveType` and the Primitive` class can create a column and add it to the group. The following is an example code that demonstrates how to use Apache Parquet API for data storage: // Create SCHEMA MessageType schema = MessageTypeParser.parseMessageType("message MySchema { required int32 id; required binary name; }"); // Create a file writer Path path = new Path("data.parquet"); ParquetWriter<Group> writer = AvroParquetWriter.builder(path) .withSchema(schema) .withCompressionCodec(CompressionCodecName.SNAPPY) .withWriteMode(ParquetFileWriter.Mode.CREATE) .build(); // Create a group object GroupBuilder groupBuilder = new GroupBuilder(schema); Group group = groupBuilder.with("id", 1) .with("name", "Alice") .build(); // Write the group object to the ParQuet file writer.write(group); // Close the file writer writer.close(); 2. Data reading mechanism: Reading data using Apache Parquet is a reverse process. You need to read the metadata information of the Parquet file first, and then analyze the data of each column based on this information. -The metadata information of the Parquet file contains the meta -data of SCHEMA and each column. You can use the `ParqueTMetAdAreadsupport` class.This category will return a `ParqueTFileReader` object, which contains data blocks and metadata information of the Parquet file. -In the `ParQuetFileRereader` object, you can obtain the number of columns and rows of schema and data blocks, and read each column data with the` ColumnReader` class. -` `ColumnReader` Class provides a reading method of different data types, which can directly read the listed data.You can use the `PrimitiveType.primitiveTypename` class to determine the data type, and read the data with the` Read` method of the `ColumnReader`. The following is a sample code that demonstrates how to use Apache Parquet API for data reading: // Open the Parquet file Path path = new Path("data.parquet"); ParquetFileReader reader = ParquetFileReader.open(ParquetIO.file(path)); // Read the metadata information of the data block ParquetMetadata parquetMetadata = reader.getFooter(); MessageType schema = parquetMetadata.getFileMetaData().getSchema(); // Create a column reader ColumnDescriptor column = schema.getColumns().get(0); ColumnDescriptor column = schema.getColumns().get(1); ColumnReader<Binary> idReader = new ColumnReaderImpl<>(column, reader); ColumnReader<Binary> nameReader = new ColumnReaderImpl<>(column, reader); // Read the data of each line int rows = parquetMetadata.getBlocks().get(0).getRowCount(); for (int i = 0; i < rows; i++) { idReader.consume(); nameReader.consume(); int id = idReader.getInteger(); String name = nameReader.getBinary().toStringUsingUTF8(); System.out.println("id: " + id + ", name: " + name); } // Close the file reader reader.close(); Through the above code example, we can understand the data storage and reading mechanism of the Apache Parquet Column framework in the Java library.Storing data with Parqueet format can improve data storage and query performance, and can be easily operated through the Java API.I hope this article can help you understand and use Apache Parquet!