Bagaimana cara memperbaiki pohon MPTT yang rusak (set bersarang) dalam database menggunakan SQL?

Inilah yang saya adaptasi dari jawaban @ Lieven, menggabungkan umpan balik dari di sini untuk kinerja yang lebih baik:

DROP PROCEDURE IF EXISTS tree_recover;

DELIMITER //

CREATE PROCEDURE tree_recover ()
MODIFIES SQL DATA
BEGIN

    DECLARE currentId, currentParentId  CHAR(36);
    DECLARE currentLeft                 INT;
    DECLARE startId                     INT DEFAULT 1;

    # Determines the max size for MEMORY tables.
    SET max_heap_table_size = 1024 * 1024 * 512;

    START TRANSACTION;

    # Temporary MEMORY table to do all the heavy lifting in,
    # otherwise performance is simply abysmal.
    CREATE TABLE `tmp_tree` (
        `id`        char(36) NOT NULL DEFAULT '',
        `parent_id` char(36)          DEFAULT NULL,
        `lft`       int(11)  unsigned DEFAULT NULL,
        `rght`      int(11)  unsigned DEFAULT NULL,
        PRIMARY KEY      (`id`),
        INDEX USING HASH (`parent_id`),
        INDEX USING HASH (`lft`),
        INDEX USING HASH (`rght`)
    ) ENGINE = MEMORY
    SELECT `id`,
           `parent_id`,
           `lft`,
           `rght`
    FROM   `tree`;

    # Leveling the playing field.
    UPDATE  `tmp_tree`
    SET     `lft`  = NULL,
            `rght` = NULL;

    # Establishing starting numbers for all root elements.
    WHILE EXISTS (SELECT * FROM `tmp_tree` WHERE `parent_id` IS NULL AND `lft` IS NULL AND `rght` IS NULL LIMIT 1) DO

        UPDATE `tmp_tree`
        SET    `lft`  = startId,
               `rght` = startId + 1
        WHERE  `parent_id` IS NULL
          AND  `lft`       IS NULL
          AND  `rght`      IS NULL
        LIMIT  1;

        SET startId = startId + 2;

    END WHILE;

    # Switching the indexes for the lft/rght columns to B-Trees to speed up the next section, which uses range queries.
    DROP INDEX `lft`  ON `tmp_tree`;
    DROP INDEX `rght` ON `tmp_tree`;
    CREATE INDEX `lft`  USING BTREE ON `tmp_tree` (`lft`);
    CREATE INDEX `rght` USING BTREE ON `tmp_tree` (`rght`);

    # Numbering all child elements
    WHILE EXISTS (SELECT * FROM `tmp_tree` WHERE `lft` IS NULL LIMIT 1) DO

        # Picking an unprocessed element which has a processed parent.
        SELECT     `tmp_tree`.`id`
          INTO     currentId
        FROM       `tmp_tree`
        INNER JOIN `tmp_tree` AS `parents`
                ON `tmp_tree`.`parent_id` = `parents`.`id`
        WHERE      `tmp_tree`.`lft` IS NULL
          AND      `parents`.`lft`  IS NOT NULL
        LIMIT      1;

        # Finding the element's parent.
        SELECT  `parent_id`
          INTO  currentParentId
        FROM    `tmp_tree`
        WHERE   `id` = currentId;

        # Finding the parent's lft value.
        SELECT  `lft`
          INTO  currentLeft
        FROM    `tmp_tree`
        WHERE   `id` = currentParentId;

        # Shifting all elements to the right of the current element 2 to the right.
        UPDATE `tmp_tree`
        SET    `rght` = `rght` + 2
        WHERE  `rght` > currentLeft;

        UPDATE `tmp_tree`
        SET    `lft` = `lft` + 2
        WHERE  `lft` > currentLeft;

        # Setting lft and rght values for current element.
        UPDATE `tmp_tree`
        SET    `lft`  = currentLeft + 1,
               `rght` = currentLeft + 2
        WHERE  `id`   = currentId;

    END WHILE;

    # Writing calculated values back to physical table.
    UPDATE `tree`, `tmp_tree`
    SET    `tree`.`lft`  = `tmp_tree`.`lft`,
           `tree`.`rght` = `tmp_tree`.`rght`
    WHERE  `tree`.`id`   = `tmp_tree`.`id`;

    COMMIT;

    DROP TABLE `tmp_tree`;

END//

DELIMITER ;

Berfungsi dengan baik dengan beberapa data pengujian, tetapi masih berjalan di 100.000 record tree saya, jadi saya belum bisa memberikan penilaian akhir. Skrip naif yang bekerja langsung pada tabel fisik memiliki kinerja yang buruk, berjalan setidaknya selama berjam-jam, lebih mungkin berhari-hari. Beralih ke tabel MEMORY sementara mempersingkat waktu menjadi sekitar satu jam, memilih indeks yang tepat memangkasnya menjadi 10 menit.