def recommendByTag(singleTag, TFIDF_tags, movies, min_fmax=10, numberOfResults=10, debug=False):
    # start by most complexity-reducing operation: filter
    # filter by the singleTag
    # remove entries with f_max < min_fmax
    df_tag = TFIDF_tags.filter(TFIDF_tags.tag == singleTag)\
                   .filter(TFIDF_tags.f_max >= min_fmax)
        
    # join to get movie title
    # order by descending TFIDF + ascending lexicographic title
    # remove unnecessary columns
    # return results limited to numberOfResults
    df = df_tag.join(movies, 'movieId')\
                .orderBy(['TF_IDF','title'], ascending=[0,1])\
                .select('movieId', 'title', 'TF_IDF')\
                .limit(numberOfResults)
    return df