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[]
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| 1 x Application (78.75%) | 626ms |
| 1 x Preparing Response (65.2%) | 518ms |
| 1 x Booting (21.25%) | 169ms |
| 1 x Routing (0.04%) | 298μs |
select * from `users` where `username` = 'nguyen-thi-cam-thu' and `users`.`deleted_at` is null limit 1| Bindings |
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select `candidates`.*, (select count(*) from `companies` inner join `bookmark_company` on `companies`.`id` = `bookmark_company`.`company_id` where `candidates`.`id` = `bookmark_company`.`candidate_id` and `companies`.`deleted_at` is null) as `bookmark_candidates_count` from `candidates` where `candidates`.`user_id` in (948)| Backtrace |
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select `professions`.*, `candidate_additional_profession`.`candidate_id` as `pivot_candidate_id`, `candidate_additional_profession`.`additional_profession_id` as `pivot_additional_profession_id` from `professions` inner join `candidate_additional_profession` on `professions`.`id` = `candidate_additional_profession`.`additional_profession_id` where `candidate_additional_profession`.`candidate_id` in (601)| Backtrace |
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select * from `contact_infos` where `contact_infos`.`user_id` in (948)| Backtrace |
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select * from `social_links` where `social_links`.`user_id` in (948)| Backtrace |
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select * from `rating` where `rating`.`user_id` in (948)| Backtrace |
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select avg(`rate`) as aggregate from `rating` where `rating`.`user_id` = 948 and `rating`.`user_id` is not null| Bindings |
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select * from `cv_prices` where (`candidate_type` = 'worker' and `candidate_need` = 'job') and (`candidate_min_star` = 0 or `candidate_min_star` = -1) and (`candidate_role` is null) limit 1| Bindings |
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select * from `users` where `username` = 'nguyen-thi-cam-thu' and `users`.`deleted_at` is null limit 1| Bindings |
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select * from `contact_infos` where `contact_infos`.`user_id` in (948)| Backtrace |
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select * from `social_links` where `social_links`.`user_id` in (948)| Backtrace |
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select `candidates`.*, (select count(*) from `companies` inner join `bookmark_company` on `companies`.`id` = `bookmark_company`.`company_id` where `candidates`.`id` = `bookmark_company`.`candidate_id` and `companies`.`deleted_at` is null) as `bookmark_candidates_count`, (select count(*) from `companies` inner join `bookmark_company` on `companies`.`id` = `bookmark_company`.`company_id` where `candidates`.`id` = `bookmark_company`.`candidate_id` and `companies`.`deleted_at` is null) as `bookmarked` from `candidates` where `candidates`.`user_id` in (948)| Backtrace |
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select * from `experiences` where `experiences`.`id` in (4)| Backtrace |
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select * from `experience_translations` where `experience_translations`.`experience_id` in (4)| Backtrace |
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select * from `education` where `education`.`id` in (3)| Backtrace |
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select * from `education_translations` where `education_translations`.`education_id` in (3)| Backtrace |
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select * from `candidate_experiences` where `candidate_experiences`.`candidate_id` in (601)| Backtrace |
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select * from `candidate_education` where `candidate_education`.`candidate_id` in (601)| Backtrace |
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select `candidate_languages`.`id`, `candidate_languages`.`name`, `candidate_language`.`candidate_id` as `pivot_candidate_id`, `candidate_language`.`candidate_language_id` as `pivot_candidate_language_id` from `candidate_languages` inner join `candidate_language` on `candidate_languages`.`id` = `candidate_language`.`candidate_language_id` where `candidate_language`.`candidate_id` in (601)| Backtrace |
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select `skills`.*, `candidate_skill`.`candidate_id` as `pivot_candidate_id`, `candidate_skill`.`skill_id` as `pivot_skill_id` from `skills` inner join `candidate_skill` on `skills`.`id` = `candidate_skill`.`skill_id` where `candidate_skill`.`candidate_id` in (601)| Backtrace |
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select * from `skill_translations` where `skill_translations`.`skill_id` in (1044, 1045, 1046, 1047)| Backtrace |
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select * from `social_links` where `social_links`.`user_id` in (601)| Backtrace |
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select `name` from `candidate_languages` inner join `candidate_language` on `candidate_languages`.`id` = `candidate_language`.`candidate_language_id` where `candidate_language`.`candidate_id` = 601| Bindings |
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select * from `candidate_references` where `candidate_references`.`candidate_id` = 601 and `candidate_references`.`candidate_id` is not null and `candidate_references`.`deleted_at` is null| Bindings |
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select `job_types`.*, `candidate_job_type`.`candidate_id` as `pivot_candidate_id`, `candidate_job_type`.`job_type_id` as `pivot_job_type_id`, `candidate_job_type`.`created_at` as `pivot_created_at`, `candidate_job_type`.`updated_at` as `pivot_updated_at` from `job_types` inner join `candidate_job_type` on `job_types`.`id` = `candidate_job_type`.`job_type_id` where `candidate_job_type`.`candidate_id` = 601| Bindings |
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select `states`.*, `candidate_desire_working_place`.`candidate_id` as `pivot_candidate_id`, `candidate_desire_working_place`.`state_id` as `pivot_state_id`, `candidate_desire_working_place`.`created_at` as `pivot_created_at`, `candidate_desire_working_place`.`updated_at` as `pivot_updated_at` from `states` inner join `candidate_desire_working_place` on `states`.`id` = `candidate_desire_working_place`.`state_id` where `candidate_desire_working_place`.`candidate_id` = 601| Bindings |
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select `countries`.*, `candidate_work_abroad_country`.`candidate_id` as `pivot_candidate_id`, `candidate_work_abroad_country`.`country_id` as `pivot_country_id`, `candidate_work_abroad_country`.`created_at` as `pivot_created_at`, `candidate_work_abroad_country`.`updated_at` as `pivot_updated_at` from `countries` inner join `candidate_work_abroad_country` on `countries`.`id` = `candidate_work_abroad_country`.`country_id` where `candidate_work_abroad_country`.`candidate_id` = 601| Bindings |
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select `countries`.*, `candidate_study_abroad_country`.`candidate_id` as `pivot_candidate_id`, `candidate_study_abroad_country`.`country_id` as `pivot_country_id`, `candidate_study_abroad_country`.`created_at` as `pivot_created_at`, `candidate_study_abroad_country`.`updated_at` as `pivot_updated_at` from `countries` inner join `candidate_study_abroad_country` on `countries`.`id` = `candidate_study_abroad_country`.`country_id` where `candidate_study_abroad_country`.`candidate_id` = 601| Bindings |
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select `cities`.*, `candidate_districts`.`candidate_id` as `pivot_candidate_id`, `candidate_districts`.`district_id` as `pivot_district_id`, `candidate_districts`.`created_at` as `pivot_created_at`, `candidate_districts`.`updated_at` as `pivot_updated_at` from `cities` inner join `candidate_districts` on `cities`.`id` = `candidate_districts`.`district_id` where `candidate_districts`.`candidate_id` = 601| Bindings |
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select * from `rating` where `rating`.`user_id` = 948 and `rating`.`user_id` is not null| Bindings |
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select * from `professional_certificates` where `professional_certificates`.`candidate_id` = 601 and `professional_certificates`.`candidate_id` is not null and `professional_certificates`.`deleted_at` is null| Bindings |
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select * from `rating` where `rating`.`user_id` = 948 and `rating`.`user_id` is not null and `type` = 'company'| Bindings |
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select * from `rating` where `rating`.`user_id` = 948 and `rating`.`user_id` is not null and `type` = 'specialist'| Bindings |
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select * from `rating` where `rating`.`user_id` = 948 and `rating`.`user_id` is not null and `type` = 'system' limit 1| Bindings |
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select count(*) as aggregate from `candidate_likes` where `candidate_likes`.`candidate_id` = 601 and `candidate_likes`.`candidate_id` is not null| Bindings |
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select * from `seos` where `page_slug` = 'candidate-details' limit 1| Bindings |
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select * from `seo_page_contents` where `seo_page_contents`.`page_id` = 21 and `seo_page_contents`.`page_id` is not null and `language_code` = 'vi' limit 1| Bindings |
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select * from `seo_page_contents` where `seo_page_contents`.`page_id` = 21 and `seo_page_contents`.`page_id` is not null and `language_code` = 'en' limit 1| Bindings |
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select `professions`.*, `candidate_additional_profession`.`candidate_id` as `pivot_candidate_id`, `candidate_additional_profession`.`additional_profession_id` as `pivot_additional_profession_id` from `professions` inner join `candidate_additional_profession` on `professions`.`id` = `candidate_additional_profession`.`additional_profession_id` where `candidate_additional_profession`.`candidate_id` = 601| Bindings |
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select * from `candidate_comments` where `candidate_comments`.`candidate_id` = 601 and `candidate_comments`.`candidate_id` is not null and `parent_id` is null order by `created_at` desc| Bindings |
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select `direction` from `languages` where `code` = 'vi' limit 1| Bindings |
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select * from `industry_types`| Backtrace |
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select * from `industry_type_translations` where `industry_type_translations`.`industry_type_id` in (1, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41)| Backtrace |
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select * from `jobs`| Backtrace |
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select * from `job_types` where `job_types`.`id` in (1, 2, 5, 6)| Backtrace |
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select * from `job_type_translations` where `job_type_translations`.`job_type_id` in (1, 2, 5, 6)| Backtrace |
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select * from `candidates`| Backtrace |
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select `job_types`.*, `candidate_job_type`.`candidate_id` as `pivot_candidate_id`, `candidate_job_type`.`job_type_id` as `pivot_job_type_id`, `candidate_job_type`.`created_at` as `pivot_created_at`, `candidate_job_type`.`updated_at` as `pivot_updated_at` from `job_types` inner join `candidate_job_type` on `job_types`.`id` = `candidate_job_type`.`job_type_id` where `candidate_job_type`.`candidate_id` in (1, 21, 27, 29, 44, 51, 60, 63, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 94, 95, 96, 97, 98, 99, 100, 102, 103, 105, 110, 111, 112, 113, 114, 115, 118, 119, 120, 122, 123, 124, 125, 126, 128, 129, 130, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 182, 183, 184, 186, 187, 188, 189, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 208, 216, 217, 218, 219, 220, 226, 227, 228, 229, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 243, 244, 246, 247, 248, 249, 250, 251, 252, 253, 254, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 317, 318, 319, 320, 321, 323, 326, 327, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 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1377, 1378, 1379, 1383, 1386)| Backtrace |
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select * from `job_type_translations` where `job_type_translations`.`job_type_id` in (1, 2, 3, 4, 5, 6, 7, 8)| Backtrace |
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select * from `countries` where `name` = 'Vietnam' limit 1| Bindings |
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select * from `states` where `country_id` = 240| Bindings |
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select * from `post_categories` where (`available_for` = 'employer' or `available_for` = 'public') order by `display_order` asc| Bindings |
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select * from `post_categories` where (`available_for` = 'candidate' or `available_for` = 'public') order by `display_order` asc| Bindings |
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select * from `post_categories` where (`available_for` = 'headhunter' or `available_for` = 'public') order by `display_order` asc| Bindings |
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select * from `industry_types`| Backtrace |
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select * from `industry_type_translations` where `industry_type_translations`.`industry_type_id` in (1, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41)| Backtrace |
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select * from `jobs`| Backtrace |
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select * from `job_types` where `job_types`.`id` in (1, 2, 5, 6)| Backtrace |
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select * from `job_type_translations` where `job_type_translations`.`job_type_id` in (1, 2, 5, 6)| Backtrace |
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select * from `candidates`| Backtrace |
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select `job_types`.*, `candidate_job_type`.`candidate_id` as `pivot_candidate_id`, `candidate_job_type`.`job_type_id` as `pivot_job_type_id`, `candidate_job_type`.`created_at` as `pivot_created_at`, `candidate_job_type`.`updated_at` as `pivot_updated_at` from `job_types` inner join `candidate_job_type` on `job_types`.`id` = `candidate_job_type`.`job_type_id` where `candidate_job_type`.`candidate_id` in (1, 21, 27, 29, 44, 51, 60, 63, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 94, 95, 96, 97, 98, 99, 100, 102, 103, 105, 110, 111, 112, 113, 114, 115, 118, 119, 120, 122, 123, 124, 125, 126, 128, 129, 130, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 182, 183, 184, 186, 187, 188, 189, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 208, 216, 217, 218, 219, 220, 226, 227, 228, 229, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 243, 244, 246, 247, 248, 249, 250, 251, 252, 253, 254, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 317, 318, 319, 320, 321, 323, 326, 327, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 510, 511, 512, 513, 514, 515, 516, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 536, 537, 538, 539, 540, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 576, 577, 578, 579, 580, 581, 582, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 632, 633, 634, 635, 636, 637, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 725, 726, 727, 728, 729, 730, 731, 732, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 751, 752, 753, 754, 755, 756, 757, 758, 760, 761, 763, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 779, 780, 781, 782, 783, 784, 785, 786, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1377, 1378, 1379, 1383, 1386)| Backtrace |
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select * from `job_type_translations` where `job_type_translations`.`job_type_id` in (1, 2, 3, 4, 5, 6, 7, 8)| Backtrace |
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select * from `countries` where `name` = 'Vietnam' limit 1| Bindings |
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| Backtrace |
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select * from `states` where `country_id` = 240| Bindings |
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| Backtrace |
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select * from `post_categories` where (`available_for` = 'employer' or `available_for` = 'public') order by `display_order` asc| Bindings |
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| Backtrace |
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select * from `post_categories` where (`available_for` = 'candidate' or `available_for` = 'public') order by `display_order` asc| Bindings |
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| Backtrace |
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select * from `post_categories` where (`available_for` = 'headhunter' or `available_for` = 'public') order by `display_order` asc| Bindings |
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| Backtrace |
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select * from `industry_types`| Backtrace |
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select * from `industry_type_translations` where `industry_type_translations`.`industry_type_id` in (1, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41)| Backtrace |
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select * from `jobs`| Backtrace |
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select * from `job_types` where `job_types`.`id` in (1, 2, 5, 6)| Backtrace |
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select * from `job_type_translations` where `job_type_translations`.`job_type_id` in (1, 2, 5, 6)| Backtrace |
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select * from `candidates`| Backtrace |
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select `job_types`.*, `candidate_job_type`.`candidate_id` as `pivot_candidate_id`, `candidate_job_type`.`job_type_id` as `pivot_job_type_id`, `candidate_job_type`.`created_at` as `pivot_created_at`, `candidate_job_type`.`updated_at` as `pivot_updated_at` from `job_types` inner join `candidate_job_type` on `job_types`.`id` = `candidate_job_type`.`job_type_id` where `candidate_job_type`.`candidate_id` in (1, 21, 27, 29, 44, 51, 60, 63, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 94, 95, 96, 97, 98, 99, 100, 102, 103, 105, 110, 111, 112, 113, 114, 115, 118, 119, 120, 122, 123, 124, 125, 126, 128, 129, 130, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 182, 183, 184, 186, 187, 188, 189, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 208, 216, 217, 218, 219, 220, 226, 227, 228, 229, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 243, 244, 246, 247, 248, 249, 250, 251, 252, 253, 254, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 317, 318, 319, 320, 321, 323, 326, 327, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 510, 511, 512, 513, 514, 515, 516, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 536, 537, 538, 539, 540, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 576, 577, 578, 579, 580, 581, 582, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 632, 633, 634, 635, 636, 637, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 725, 726, 727, 728, 729, 730, 731, 732, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 751, 752, 753, 754, 755, 756, 757, 758, 760, 761, 763, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 779, 780, 781, 782, 783, 784, 785, 786, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1377, 1378, 1379, 1383, 1386)| Backtrace |
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select * from `job_type_translations` where `job_type_translations`.`job_type_id` in (1, 2, 3, 4, 5, 6, 7, 8)| Backtrace |
|
select * from `countries` where `name` = 'Vietnam' limit 1| Bindings |
|
| Backtrace |
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select * from `states` where `country_id` = 240| Bindings |
|
| Backtrace |
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select * from `post_categories` where (`available_for` = 'employer' or `available_for` = 'public') order by `display_order` asc| Bindings |
|
| Backtrace |
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select * from `post_categories` where (`available_for` = 'candidate' or `available_for` = 'public') order by `display_order` asc| Bindings |
|
| Backtrace |
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select * from `post_categories` where (`available_for` = 'headhunter' or `available_for` = 'public') order by `display_order` asc| Bindings |
|
| Backtrace |
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select * from `industry_types`| Backtrace |
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select * from `industry_type_translations` where `industry_type_translations`.`industry_type_id` in (1, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41)| Backtrace |
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select * from `jobs`| Backtrace |
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select * from `job_types` where `job_types`.`id` in (1, 2, 5, 6)| Backtrace |
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select * from `job_type_translations` where `job_type_translations`.`job_type_id` in (1, 2, 5, 6)| Backtrace |
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select * from `candidates`| Backtrace |
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select `job_types`.*, `candidate_job_type`.`candidate_id` as `pivot_candidate_id`, `candidate_job_type`.`job_type_id` as `pivot_job_type_id`, `candidate_job_type`.`created_at` as `pivot_created_at`, `candidate_job_type`.`updated_at` as `pivot_updated_at` from `job_types` inner join `candidate_job_type` on `job_types`.`id` = `candidate_job_type`.`job_type_id` where `candidate_job_type`.`candidate_id` in (1, 21, 27, 29, 44, 51, 60, 63, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 94, 95, 96, 97, 98, 99, 100, 102, 103, 105, 110, 111, 112, 113, 114, 115, 118, 119, 120, 122, 123, 124, 125, 126, 128, 129, 130, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 182, 183, 184, 186, 187, 188, 189, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 208, 216, 217, 218, 219, 220, 226, 227, 228, 229, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 243, 244, 246, 247, 248, 249, 250, 251, 252, 253, 254, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 317, 318, 319, 320, 321, 323, 326, 327, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 510, 511, 512, 513, 514, 515, 516, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 536, 537, 538, 539, 540, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 576, 577, 578, 579, 580, 581, 582, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 632, 633, 634, 635, 636, 637, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 725, 726, 727, 728, 729, 730, 731, 732, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 751, 752, 753, 754, 755, 756, 757, 758, 760, 761, 763, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 779, 780, 781, 782, 783, 784, 785, 786, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1377, 1378, 1379, 1383, 1386)| Backtrace |
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select * from `job_type_translations` where `job_type_translations`.`job_type_id` in (1, 2, 3, 4, 5, 6, 7, 8)| Backtrace |
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select * from `countries` where `name` = 'Vietnam' limit 1| Bindings |
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select * from `states` where `country_id` = 240| Bindings |
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select * from `post_categories` where (`available_for` = 'employer' or `available_for` = 'public') order by `display_order` asc| Bindings |
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select * from `post_categories` where (`available_for` = 'candidate' or `available_for` = 'public') order by `display_order` asc| Bindings |
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select * from `post_categories` where (`available_for` = 'headhunter' or `available_for` = 'public') order by `display_order` asc| Bindings |
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