c++ - 使用 Rfc4180CsvParser 将 CSV 导入 Vertica 并排除标题行

Question

通过 Rfc4180CsvParser 导入数据时是否可以排除标题行？ COPY命令有一个 SKIP选项，但在使用 Vertica SDK 中提供的 CSV 解析器时，该选项似乎不起作用。

背景

作为背景， COPY 命令本身不会读取 CSV 文件。对于简单的 CSV 文件，可以说 COPY schema.table FROM '/data/myfile.csv' DELIMITER ',' ENCLOSED BY '"';但对于具有嵌入引号的字符串值的数据文件，这将失败。

添加ESCAPE AS '"'将生成错误ERROR 3169: ENCLOSED BY and ESCAPE AS can not be the same value 。这是一个问题，因为 CSV 值被 " 括起来并转义。 .

Vertica SDK CsvParser 扩展来救援

Vertica 在 /opt/vertica/sdk/examples 下提供了一个 SDK可以编译为扩展的 C++ 程序。其中之一是 /opt/vertica/sdk/examples/ParserFunctions/Rfc4180CsvParser.cpp 。

这非常有效，如下所示:

 cd /opt/vertica/sdk/examples
 make clean
 vsql 
 ==> CREATE LIBRARY Rfc4180CsvParserLib AS '/opt/vertica/sdk/examples/build/Rfc4180CsvParser.so';
 ==> COPY myschema.mytable FROM '/data/myfile.csv' WITH PARSER Rfc4180CsvParser();

问题

上面的效果很好除了它将数据文件的第一行作为一行导入。 COPY命令有一个 SKIP 1选项，但这不适用于解析器。

问题

可以编辑Rfc4180CsvParser.cpp跳过第一行，或者更好的是，采用一些参数来指定要跳过的行数？

程序只有 135 行，但我不知道在哪里/如何做这个切口。提示？

复制下面的整个程序，因为我没有看到可链接到的公共(public)存储库...

Rfc4180CsvParser.cpp

/* Copyright (c) 2005 - 2012 Vertica, an HP company -*- C++ -*- */

#include "Vertica.h"
#include "StringParsers.h"
#include "csv.h"

using namespace Vertica;

// Note, the class template is mostly for demonstration purposes,
// so that the same class can use each of two string-parsers.
// Custom parsers can also just pick a string-parser to use.

/**
 * A parser that parses something approximating the "official" CSV format
 * as defined in IETF RFC-4180:  <http://tools.ietf.org/html/rfc4180>
 * Oddly enough, many "CSV" files don't actually conform to this standard
 * for one reason or another.  But for sources that do, this parser should
 * be able to handle the data.
 * Note that the CSV format does not specify how to handle different
 * data types; it is entirely a string-based format.
 * So we just use standard parsers based on the corresponding column type.
 */
template <class StringParsersImpl>
class LibCSVParser : public UDParser {
public:
    LibCSVParser() : colNum(0) {}

    // Keep a copy of the information about each column.
    // Note that Vertica doesn't let us safely keep a reference to
    // the internal copy of this data structure that it shows us.
    // But keeping a copy is fine.
    SizedColumnTypes colInfo;

    // An instance of the class containing the methods that we're
    // using to parse strings to the various relevant data types
    StringParsersImpl sp;

    /// Current column index
    size_t colNum;

    /// Parsing state for libcsv
    struct csv_parser parser;

    // Format strings
    std::vector<std::string> formatStrings;

    /**
     * Given a field in string form (a pointer to the first character and
     * a length), submit that field to Vertica.
     * `colNum` is the column number from the input file; how many fields
     * it is into the current record.
     */
    bool handleField(size_t colNum, char* start, size_t len) {
        if (colNum >= colInfo.getColumnCount()) {
            // Ignore column overflow
            return false;
        }
        // Empty colums are null.
        if (len==0) {
            writer->setNull(colNum);
            return true;
        } else {
            return parseStringToType(start, len, colNum, colInfo.getColumnType(c
olNum), writer, sp);
        }
    }

    static void handle_record(void *data, size_t len, void *p) {
        static_cast<LibCSVParser*>(p)->handleField(static_cast<LibCSVParser*>(p)
->colNum++, (char*)data, len);
    }

    static void handle_end_of_row(int c, void *p) {
        // Ignore 'c' (the terminating character); trust that it's correct
        static_cast<LibCSVParser*>(p)->colNum = 0;
        static_cast<LibCSVParser*>(p)->writer->next();
    }

    virtual StreamState process(ServerInterface &srvInterface, DataBuffer &input
, InputState input_state) {
        size_t processed;
        while ((processed = csv_parse(&parser, input.buf + input.offset, input.s
ize - input.offset,
                handle_record, handle_end_of_row, this)) > 0) {
            input.offset += processed;
        }

        if (input_state == END_OF_FILE && input.size == input.offset) {
            csv_fini(&parser, handle_record, handle_end_of_row, this);
            return DONE;
        }

        return INPUT_NEEDED;
    }

    virtual void setup(ServerInterface &srvInterface, SizedColumnTypes &returnTy
pe);
    virtual void destroy(ServerInterface &srvInterface, SizedColumnTypes &return
Type) {
        csv_free(&parser);
    }
};

template <class StringParsersImpl>
void LibCSVParser<StringParsersImpl>::setup(ServerInterface &srvInterface, Sized
ColumnTypes &returnType) {
    csv_init(&parser, CSV_APPEND_NULL);
    colInfo = returnType;
}

template <>
void LibCSVParser<FormattedStringParsers>::setup(ServerInterface &srvInterface, 
SizedColumnTypes &returnType) {
    csv_init(&parser, CSV_APPEND_NULL);
    colInfo = returnType;
    if (formatStrings.size() != returnType.getColumnCount()) {
        formatStrings.resize(returnType.getColumnCount(), "");
    }
    sp.setFormats(formatStrings);
}

template <class StringParsersImpl>
class LibCSVParserFactoryTmpl : public ParserFactory {
public:
    virtual void plan(ServerInterface &srvInterface,
            PerColumnParamReader &perColumnParamReader,
            PlanContext &planCtxt) {}

    virtual UDParser* prepare(ServerInterface &srvInterface,
            PerColumnParamReader &perColumnParamReader,
            PlanContext &planCtxt,
            const SizedColumnTypes &returnType)
    {
        return vt_createFuncObj(srvInterface.allocator,
                LibCSVParser<StringParsersImpl>);
    }
};

typedef LibCSVParserFactoryTmpl<StringParsers> LibCSVParserFactory;
RegisterFactory(LibCSVParserFactory);

typedef LibCSVParserFactoryTmpl<FormattedStringParsers> FormattedLibCSVParserFac
tory;
RegisterFactory(FormattedLibCSVParserFactory);

Answer 1

快速而肮脏的方法就是对其进行硬编码。它使用对handle_end_of_row的回调。跟踪行号，但不处理第一行。类似于:

static void handle_end_of_row(int c, void *ptr) {
    // Ignore 'c' (the terminating character); trust that it's correct
    LibCSVParser *p = static_cast<LibCSVParser*>(ptr);
    p->colNum = 0;

    if (rowcnt <= 0) {
        p->bad_field = "";
        rowcnt++;
    } else if (p->bad_field.empty()) {
        p->writer->next();
    } else {
        // libcsv doesn't give us the whole row to reject.
        // So just write to the log.
        // TODO: Come up with something more clever.
        if (p->currSrvInterface) {
            p->currSrvInterface->log("Invalid CSV field value: '%s'  Row skipped.",
                                    p->bad_field.c_str());
        }
        p->bad_field = "";
    }
}

此外，最好在process中初始化rownum = 0，因为我认为它会为COPY语句中的每个文件调用它。可能有更聪明的方法来做到这一点。基本上，这只会处理记录然后丢弃它。

至于一般支持SKIP...请参阅TraditionalCSVParser了解如何处理参数传递。您必须将其添加到解析器因子 prepare 并将值发送到 LibCSVParser 类并覆盖 getParameterType。然后在 LibCSVParser 中，您需要在构造函数中接受参数，并修改 process 以跳过前 skip 行。然后使用该值而不是上面的硬编码 0。