google-bigquery jaro_winkle_distanceのUDF

Question

私はjaro_winkle_distanceを計算する次のUDFコードです jsonテストデータでテストするとうまくいくようですが、google-bigquery UIで呼び出そうとすると、一貫してスコア0。たとえ自己結合であっても です。

入力：

[ 
{a: "Liu",b:"Lau"}, 
{a: "John",b:"Jone"}] 

出力：

[ 
    { 
    "scr": 80 
    }, 
    { 
    "scr": 87 
    } 
] 

SQL：

CREATE TEMP FUNCTION 
    jwd(a STRING, 
    b STRING) 
    RETURNS INT64 
    LANGUAGE js AS """ 
    // Assumes 'doInterestingStuff' is defined in one of the library files. 
    //return doInterestingStuff(a, b); 
    return jaro_winkler_distance(a,b); 
""" OPTIONS (library="gs://kayama808/javascript/jaro_winkler_google_UDF.js"); 
SELECT 
    x.name name1, 
    jwd(x.name, 
    x.name) scr 
FROM 
    babynames.usa_1910_2013_copy x 
WHERE 
    x.gender = 'F' and x.number >= 1000 and x.state = 'CA' 
ORDER BY 
    scr DESC; 

http://storage.googleapis.com/bigquery-udf-test-tool/testtool.html

https://storage.cloud.google.com/kayama808/javascript/jaro_winkler_google_UDF.js?_ga=1.184402278.1320598031.1475534357

Answer 1

以下を試してください。 O）また

CREATE TEMP FUNCTION jwd(a STRING, b STRING) 
    RETURNS INT64 
    LANGUAGE js AS """ 
/* JS implementation of the strcmp95 C function written by 
Bill Winkler, George McLaughlin, Matt Jaro and Maureen Lynch, 
released in 1994 (http://web.archive.org/web/20100227020019/http://www.census.gov/geo/msb/stand/strcmp.c). 

a and b should be strings. Always performs case-insensitive comparisons 
and always adjusts for long strings. */ 

var jaro_winkler_adjustments = { 
    'A': 'E', 
    'A': 'I', 
    'A': 'O', 
    'A': 'U', 
    'B': 'V', 
    'E': 'I', 
    'E': 'O', 
    'E': 'U', 
    'I': 'O', 
    'I': 'U', 
    'O': 'U', 
    'I': 'Y', 
    'E': 'Y', 
    'C': 'G', 
    'E': 'F', 
    'W': 'U', 
    'W': 'V', 
    'X': 'K', 
    'S': 'Z', 
    'X': 'S', 
    'Q': 'C', 
    'U': 'V', 
    'M': 'N', 
    'L': 'I', 
    'Q': 'O', 
    'P': 'R', 
    'I': 'J', 
    '2': 'Z', 
    '5': 'S', 
    '8': 'B', 
    '1': 'I', 
    '1': 'L', 
    '0': 'O', 
    '0': 'Q', 
    'C': 'K', 
    'G': 'J', 
    'E': ' ', 
    'Y': ' ', 
    'S': ' ' 
}; 

    if (!a || !b) { return 0.0; } 

    a = a.trim().toUpperCase(); 
    b = b.trim().toUpperCase(); 
    var a_len = a.length; 
    var b_len = b.length; 
    var a_flag = []; var b_flag = []; 
    var search_range = Math.floor(Math.max(a_len, b_len)/2) - 1; 
    var minv = Math.min(a_len, b_len); 

    // Looking only within the search range, count and flag the matched pairs. 
    var Num_com = 0; 
    var yl1 = b_len - 1; 
    for (var i = 0; i < a_len; i++) { 
    var lowlim = (i >= search_range) ? i - search_range : 0; 
    var hilim = ((i + search_range) <= yl1) ? (i + search_range) : yl1; 
    for (var j = lowlim; j <= hilim; j++) { 
     if (b_flag[j] !== 1 && a[j] === b[i]) { 
     a_flag[j] = 1; 
     b_flag[i] = 1; 
     Num_com++; 
     break; 
     } 
    } 
    } 

    // Return if no characters in common 
    if (Num_com === 0) { return 0.0; } 

    // Count the number of transpositions 
    var k = 0; var N_trans = 0; 
    for (var i = 0; i < a_len; i++) { 
    if (a_flag[i] === 1) { 
     var j; 
     for (j = k; j < b_len; j++) { 
     if (b_flag[j] === 1) { 
      k = j + 1; 
      break; 
     } 
     } 
     if (a[i] !== b[j]) { N_trans++; } 
    } 
    } 
    N_trans = Math.floor(N_trans/2); 

    // Adjust for similarities in nonmatched characters 
    var N_simi = 0; var adjwt = jaro_winkler_adjustments; 
    if (minv > Num_com) { 
    for (var i = 0; i < a_len; i++) { 
     if (!a_flag[i]) { 
     for (var j = 0; j < b_len; j++) { 
      if (!b_flag[j]) { 
      if (adjwt[a[i]] === b[j]) { 
       N_simi += 3; 
       b_flag[j] = 2; 
       break; 
      } 
      } 
     } 
     } 
    } 
    } 

    var Num_sim = (N_simi/10.0) + Num_com; 

    // Main weight computation 
    var weight = Num_sim/a_len + Num_sim/b_len + (Num_com - N_trans)/Num_com; 
    weight = weight/3; 

    // Continue to boost the weight if the strings are similar 
    if (weight > 0.7) { 
    // Adjust for having up to the first 4 characters in common 
    var j = (minv >= 4) ? 4 : minv; 
    var i; 
    for (i = 0; (i < j) && a[i] === b[i]; i++) { } 
    if (i) { weight += i * 0.1 * (1.0 - weight) }; 

    // Adjust for long strings. 
    // After agreeing beginning chars, at least two more must agree 
    // and the agreeing characters must be more than half of the 
    // remaining characters. 
    if (minv > 4 && Num_com > i + 1 && 2 * Num_com >= minv + i) { 
     weight += (1 - weight) * ((Num_com - i - 1)/(a_len * b_len - i*2 + 2)); 
    } 
    } 

    return Math.round(weight*100); 

"""; 

SELECT 
    name1, name2, 
    jwd(name1, name2) scr 
FROM -- babynames.usa_1910_2013_copy x 
    (
    select "Liu" as name1, "Lau" as name2 union all 
    select "Liu" as name1, "Liu" as name2 union all 
    select "John" as name1, "Jone" as name2 
) x 
ORDER BY scr DESC 

を：：予想通り

name1 name2 scr 
Liu  Liu  100 
John Jone  87 
Liu  Lau  80 

がうまくいけば、あなたは外部のlibファイルに戻ってそれを置くことができるようになりますように、それは結果で動作します私はちょうどダブルあなたのjaro_winkler_google_UDF2をチェックしました.jsファイルを開き、このファイルに問題があることを明確に確認します。
私の答えに

をコードを使用してこのファイルを修正したり、ちょうどそれ

var a = r.a; 
var b = r.b; 

とのコメントを外し

//jaro_winkler.distance = function(a, b) { 

//return Math.round(weight*100) 

にラインの下に削除し、

jaro_winkler_distance=function(r, emit) { 

emit(weight); 

それに emitを持つすべてのコメント

あなたは大丈夫でしょう！