flink sql 处理自定义json解析

最近要把公司flink nginx 日志入库的代码，修改成flink sql的方式执行。这样日志的入库通过sql更加方便。

但是flink sql没有提供对json的解析方式，而nginx日志又是json字符串无法完全使用sql来完成日志的入库。

因此，需要修改flink来完成json的自定义解析。

首先

定义source表

CREATE TABLE kafka (
  json_data string,
  type string,  ts TIMESTAMP(3) METADATA FROM 'timestamp'
) WITH (
  'connector' = 'kafka',
  'topic' = 'nginxlog',
  'properties.bootstrap.servers' = '127.0.0.1:9092',
  'properties.group.id' = 'flink-kafka',
  'scan.startup.mode' = 'earliest-offset',
  'format' = 'json'
)

定义sink表

CREATE TABLE hdfs (
  request_url STRING,
  resp_code INT,
  ...
)  WITH (
  'connector' = 'filesystem',          
  'path' = 'file:///path/to/whatever', 
  'format' = 'orc', 
  ...
)

定义一个json解析的表（涉及方法，后面有实现）

'table' = 'kafka'读取的数据表
'stream' = 'org.apache.flink.streaming.JsonStreamTableProcessFunction' json解析类
json_data$reuest_url 为
{
   "json_data": {
       "reuest_url": "http://www.baidu.com"
   }
}
StreamTableUtil.createStreamTable(fsTableEnv, "CREATE TABLE to_json (\n" +
                "  json_data$reuest_url STRING,\n" +
                "  json_data$resp_code INT\n" +
                ") WITH (\n" +
                " 'table' = 'kafka',\n" +
                " 'stream' = 'org.apache.flink.streaming.JsonStreamTableProcessFunction'\n" +
                ")");

执行入库sql

insert into hdfs select * from to_json

下面是createStreamTable的实现

package org.apache.flink.streaming;

import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.table.api.ApiExpression;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.api.internal.TableEnvironmentInternal;
import org.apache.flink.table.catalog.CatalogTable;
import org.apache.flink.table.data.RowData;
import org.apache.flink.table.delegation.Parser;
import org.apache.flink.table.operations.Operation;
import org.apache.flink.table.operations.ddl.CreateTableOperation;
import org.apache.flink.table.runtime.typeutils.InternalTypeInfo;
import org.apache.flink.table.types.logical.RowType;

import java.lang.reflect.Constructor;
import java.util.List;
import java.util.Map;
import java.util.UUID;
import java.util.stream.Collectors;

import static org.apache.flink.table.api.Expressions.$;

public final class StreamTableUtil {

    private StreamTableUtil() {

    }

    public static void createStreamTable(StreamTableEnvironment fsTableEnv, String sql) throws Exception {
        TableEnvironmentInternal tableEnvironment = (TableEnvironmentInternal) fsTableEnv;
        Parser parser = tableEnvironment.getParser();
        List parse = parser.parse(sql);
        CreateTableOperation operation = (CreateTableOperation) parse.get(0);
        String tableName = operation.getTableIdentifier().getObjectName();
        CatalogTable catalogTable = operation.getCatalogTable();

        //create tmp table
        String tmpTable = "tmp" + UUID.randomUUID().toString().replaceAll("\\-", "");
        fsTableEnv.executeSql(sql.replace(tableName, tmpTable));

        Map properties = catalogTable.getOptions();
        String fromTable = properties.get("table");
        Class streamClass = (Class) Class.forName(properties.get("stream"));
        createStreamTable(fsTableEnv, fromTable, catalogTable, tableName, streamClass);
    }

    private static void createStreamTable(StreamTableEnvironment fsTableEnv, String fromTable, CatalogTable toCatalogTable, String toTable, Class streamClass) throws Exception {
        Table fromCatalogTable = fsTableEnv.sqlQuery("select * from " + fromTable);
        DataStream stream = fsTableEnv.toAppendStream(fromCatalogTable, RowData.class);
        RowType fromTableRowType = new RowType(fromCatalogTable.getSchema().getTableColumns().stream()
                .map(e -> new RowType.RowField(e.getName(), e.getType().getLogicalType(), null))
                .collect(Collectors.toList()));
        RowType toTableRowType = new RowType(toCatalogTable.getSchema().getTableColumns().stream()
                .map(e -> new RowType.RowField(e.getName(), e.getType().getLogicalType(), null))
                .collect(Collectors.toList()));
        Constructor constructor = streamClass.getDeclaredConstructor(RowType.class, RowType.class);
        InternalTypeInfo internalTypeInfo = InternalTypeInfo.of(toTableRowType);
        DataStream out = stream.process(constructor.newInstance(fromTableRowType, toTableRowType), internalTypeInfo);
        List apiExpressionList = toTableRowType.getFieldNames().stream().map(e -> $(e)).collect(Collectors.toList());
        fsTableEnv.createTemporaryView(toTable, out, apiExpressionList.toArray(new ApiExpression[0]));
    }
}

定义stream table处理的父类

package org.apache.flink.streaming;

import org.apache.flink.streaming.api.functions.ProcessFunction;
import org.apache.flink.table.data.RowData;
import org.apache.flink.table.types.logical.RowType;

public abstract class StreamTableProcessFunction extends ProcessFunction {

    private RowType fromTableRowType;
    private RowType toTableRowType;

    public RowType getFromTableRowType() {
        return fromTableRowType;
    }

    public RowType getToTableRowType() {
        return toTableRowType;
    }

    public StreamTableProcessFunction(RowType fromTableRowType, RowType toTableRowType) {
        this.fromTableRowType = fromTableRowType;
        this.toTableRowType = toTableRowType;
    }
}

实现json解析的子类

package org.apache.flink.streaming;

import com.google.gson.Gson;
import com.google.gson.JsonObject;
import com.google.gson.JsonPrimitive;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.table.data.GenericRowData;
import org.apache.flink.table.data.RowData;
import org.apache.flink.table.data.binary.BinaryStringData;
import org.apache.flink.table.types.logical.RowType;
import org.apache.flink.util.Collector;

import java.util.*;

public class JsonStreamTableProcessFunction extends StreamTableProcessFunction {

    private Gson gson;

    public JsonStreamTableProcessFunction(RowType fromTableRowType, RowType toTableRowType) {
        super(fromTableRowType, toTableRowType);
    }

    @Override
    public void open(Configuration parameters) throws Exception {
        gson = new Gson();
    }

    @Override
    public void processElement(RowData value, Context ctx, Collector out) throws Exception {
        Map fieldIndex = new LinkedHashMap<>();
        for (int i = 0; i < getFromTableRowType().getFields().size(); i++) {
            RowType.RowField rowField = getFromTableRowType().getFields().get(i);
            fieldIndex.put(rowField.getName(), i);
        }
        GenericRowData rowData = new GenericRowData(getToTableRowType().getFieldCount());
        List fields = getToTableRowType().getFields();
        for (int f = 0; f < fields.size(); f++) {
            RowType.RowField rowField = fields.get(f);
            String[] split = rowField.getName().split("\\$");
            String key = split[0];
            Integer idx = fieldIndex.get(key);
            //针对nginx request_body 二进制数据转义
            String json = value.getString(idx).toString().replaceAll("\\\\x", "\\\\\\\\x");
            JsonObject jsonObject = gson.fromJson(json, JsonObject.class);
            for (int i = 1; i < split.length; i++) {
                String k = split[i];
                if (i < split.length - 1) {
                    jsonObject = jsonObject.get(k).getAsJsonObject();
                } else {
                    if (Integer.class.isAssignableFrom(rowField.getType().getDefaultConversion())) {
                        try {
                            rowData.setField(f, jsonObject.get(k).getAsInt());
                        } catch (Exception e) {
                        }
                    } else if (Float.class.isAssignableFrom(rowField.getType().getDefaultConversion())) {
                        try {
                            rowData.setField(f, jsonObject.get(k).getAsFloat());
                        } catch (Exception e) {
                        }
                    } else if (Double.class.isAssignableFrom(rowField.getType().getDefaultConversion())) {
                        try {
                            rowData.setField(f, jsonObject.get(k).getAsDouble());
                        } catch (Exception e) {
                        }
                    } else {
                        String ret = jsonObject.get(k).toString();
                        rowData.setField(f, new BinaryStringData(ret));
                    }
                }
            }
        }
        out.collect(rowData);
    }
}