oracle json_value vs. json_table 解释查询计划
oracle json_value vs. json_table explain query plan
我有一个查询，它已经写了一段时间了。基本上是一个使用 json_table 函数的物化视图。
最近，自从我们迁移到 Oracle 19c 后，MV 有时可以工作，有时则不能。
我使用 oracle json_value 函数重写了该查询。
查看查询计划，我发现使用 json_table 的查询要慢得多，但我不理解所有这些数据。
谁能解释一下字节、CPU、时间等
是什么意思
这正在使用 json_value
EXPLAIN PLAN for
SELECT
JSON_VALUE(response, '$.ErrorRecord[0].xNumber') xNumber,
JSON_VALUE(response, '$.ErrorRecord[0]."error field"') ERROR_FIELD,
JSON_VALUE(response, '$.ErrorRecord[0]."value of field in error"') VALUE_OF_FIELD_IN_ERROR,
JSON_VALUE(response, '$.ErrorRecord[0]."error description"') ERROR_DESCRIPTION,
JSON_VALUE(request, '$.Status') STATUS,
sf.sv_code CENTER,
TO_CHAR(arr.created_date_time, 'YYYYMMDD' ) DATE_OCCURANCE
FROM
aud_request_response arr ,
person p,
rep_mapper_svc_fco sf,
rep_mapper_interface_error re
WHERE
JSON_VALUE(response, '$.ErrorRecord[0].xNumber') = p.registration_number (+)
AND arr.response.Status = 'Error'
AND arr.request.interfaceName = 'CLAIMS'
AND JSON_VALUE(request, '$.DataRecord[0].ACO') = sf.fco_code(+)
AND arr.request.interfaceName = re.interface_name
AND coalesce(sf.svc_code,'ATH')
IN ('XS','YS','XZ','ZS','ASD')
GROUP BY
sf.sv_code,
JSON_VALUE(request, '$.DataRecord[0].ACO'),
arr.request.interfaceName,
JSON_VALUE(request, '$.Status'),
JSON_VALUE(response, '$.ErrorRecord[0]."error field"'),
arr.created_date_time,
arr.updated_date_time,
JSON_VALUE(response, '$.ErrorRecord[0]."value of field in error"'),
JSON_VALUE(response, '$.ErrorRecord[0]."error description"'),
JSON_VALUE(response, '$.ErrorRecord[0].xNumber') ;
SELECT * FROM table(DBMS_XPLAN.DISPLAY);
Plan hash value: 241534218
------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1094 | 871K| | 1877K (1)| 00:01:14 |
| 1 | HASH GROUP BY | | 1094 | 871K| 4688K| 1877K (1)| 00:01:14 |
| 2 | NESTED LOOPS OUTER | | 5259 | 4190K| | 1877K (1)| 00:01:14 |
|* 3 | FILTER | | | | | | |
|* 4 | HASH JOIN RIGHT OUTER| | 5259 | 4139K| | 1866K (1)| 00:01:13 |
| 5 | TABLE ACCESS FULL | REP_MAPPER_SVC_FCO | 85 | 680 | | 3 (0)| 00:00:01 |
|* 6 | HASH JOIN RIGHT SEMI| | 5259 | 4098K| | 1866K (1)| 00:01:13 |
|* 7 | TABLE ACCESS FULL | REP_MAPPER_INTERFACE_ERROR | 33 | 363 | | 5 (0)| 00:00:01 |
|* 8 | TABLE ACCESS FULL | AUD_REQUEST_RESPONSE | 5259 | 4041K| | 1866K (1)| 00:01:13 |
|* 9 | INDEX UNIQUE SCAN | PER_ANBR_IDX | 1 | 10 | | 2 (0)| 00:00:01 |
------------------------------------------------------------------------------------------------------------------
通过使用json_table
EXPLAIN PLAN for
SELECT
jtresponse.xNumber as xNumber,
jtresponse.error_field as ERROR_FIELD,
replace(jtresponse.value_of_field_in_error, ',interfaceName=INTERFACES','') as VALUE_OF_FIELD_IN_ERROR,
jtresponse.error_description as ERROR_DESCRIPTION,
trim(arr.response.Status) as STATUS,
sf.sv_code as CENTER,
TO_CHAR(arr.created_date_time, 'YYYYMMDD' ) as DATE_OCCURANCE
from
aud_request_response arr,
person p,
rep_mapper_svc_fco sf,
rep_mapper_interface_error re,
json_table(response, '$'
COLUMNS (
nested path '$.ErrorRecord[*]' columns (
aNumber path '$.xNumber' null on error,
error_field path '$."error field"' null on error,
value_of_field_in_error path '$."value of field in error"' null on error,
error_description path '$."error description"' null on error
))) jtresponse
,json_table(request, '$'
COLUMNS (
nested path '$.DataRecord[*]' columns (
fileControl path '$.ACO' null on error
))) jtrequest
where jtrequest.fileControl =sf.fco_code(+)
and arr.request.interfaceName = 'CLAIMS'
and arr.request.interfaceName = re.interface_name
and jtresponse.xNumber = p.registration_number (+)
and arr.response.Status='Error'
and coalesce(sf.sv_code,'ATH') in('XS','YS','XZ','ZS','ASD')
GROUP BY
sv_code,
jtrequest.fileControl,
arr.request.interfaceName,
arr.response.Status,
jtresponse.error_field,
arr.created_date_time,
arr.updated_date_time,
jtresponse.value_of_field_in_error,
jtresponse.error_description,
jtresponse.xNumber;
SELECT * FROM table(DBMS_XPLAN.DISPLAY);
Plan hash value: 834586449
--------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
--------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 350G| 260T| | 1908M (2)| 20:42:27 |
| 1 | HASH GROUP BY | | 350G| 260T| 290T| 1908M (2)| 20:42:27 |
| 2 | NESTED LOOPS | | 350G| 260T| | 1168M (1)| 12:40:35 |
|* 3 | FILTER | | | | | | |
|* 4 | HASH JOIN RIGHT OUTER | | 42M| 32G| | 2009K (1)| 00:01:19 |
| 5 | TABLE ACCESS FULL | REP_MAPPER_SVC_FCO | 85 | 680 | | 3 (0)| 00:00:01 |
| 6 | NESTED LOOPS | | 42M| 32G| | 2009K (1)| 00:01:19 |
|* 7 | HASH JOIN RIGHT SEMI | | 5259 | 4098K| | 1866K (1)| 00:01:13 |
|* 8 | TABLE ACCESS FULL | REP_MAPPER_INTERFACE_ERROR | 33 | 363 | | 5 (0)| 00:00:01 |
|* 9 | TABLE ACCESS FULL | AUD_REQUEST_RESPONSE | 5259 | 4041K| | 1866K (1)| 00:01:13 |
| 10 | JSONTABLE EVALUATION | | | | | | |
| 11 | JSONTABLE EVALUATION | | | | | | |
--------------------------------------------------------------------------------------------------------------------
谢谢！
首先：两个查询不等价！
json_value 查询获取 DataRecord 和 ErrorRecord 数组中的第一个条目。使用 json_table 数据库为数组中的每个元素生成一行。
我发现 jtrequest 和 jtresponse 之间没有连接。所以查询正在生成这些数组的笛卡尔积。即，它为每个文档的第一个数组中的每个元素和第二个数组中的每个元素创建一行。
rows/bytes/time 列都是估计值。优化器根据 table 统计数据认为这是 rows/size data/query 持续时间。
计划中的第一行是（估计）查询 return。所以对于 json_table，它估计：
- 350G => 350 十亿 行
- 260T => 260 太字节 数据
- 20:42:27 => 20+ 小时 运行时间
由于多种原因，这些数字可能是错误的，但即使它们超过 1000 倍，您仍在查看大量数据。
我认为您需要弄清楚原始查询的目的 - 特别是它生成两个数组的笛卡尔积的原因。这会迅速增加数据量。
我有一个查询，它已经写了一段时间了。基本上是一个使用 json_table 函数的物化视图。
最近，自从我们迁移到 Oracle 19c 后，MV 有时可以工作，有时则不能。 我使用 oracle json_value 函数重写了该查询。 查看查询计划，我发现使用 json_table 的查询要慢得多，但我不理解所有这些数据。
谁能解释一下字节、CPU、时间等
是什么意思这正在使用 json_value
EXPLAIN PLAN for
SELECT
JSON_VALUE(response, '$.ErrorRecord[0].xNumber') xNumber,
JSON_VALUE(response, '$.ErrorRecord[0]."error field"') ERROR_FIELD,
JSON_VALUE(response, '$.ErrorRecord[0]."value of field in error"') VALUE_OF_FIELD_IN_ERROR,
JSON_VALUE(response, '$.ErrorRecord[0]."error description"') ERROR_DESCRIPTION,
JSON_VALUE(request, '$.Status') STATUS,
sf.sv_code CENTER,
TO_CHAR(arr.created_date_time, 'YYYYMMDD' ) DATE_OCCURANCE
FROM
aud_request_response arr ,
person p,
rep_mapper_svc_fco sf,
rep_mapper_interface_error re
WHERE
JSON_VALUE(response, '$.ErrorRecord[0].xNumber') = p.registration_number (+)
AND arr.response.Status = 'Error'
AND arr.request.interfaceName = 'CLAIMS'
AND JSON_VALUE(request, '$.DataRecord[0].ACO') = sf.fco_code(+)
AND arr.request.interfaceName = re.interface_name
AND coalesce(sf.svc_code,'ATH')
IN ('XS','YS','XZ','ZS','ASD')
GROUP BY
sf.sv_code,
JSON_VALUE(request, '$.DataRecord[0].ACO'),
arr.request.interfaceName,
JSON_VALUE(request, '$.Status'),
JSON_VALUE(response, '$.ErrorRecord[0]."error field"'),
arr.created_date_time,
arr.updated_date_time,
JSON_VALUE(response, '$.ErrorRecord[0]."value of field in error"'),
JSON_VALUE(response, '$.ErrorRecord[0]."error description"'),
JSON_VALUE(response, '$.ErrorRecord[0].xNumber') ;
SELECT * FROM table(DBMS_XPLAN.DISPLAY);
Plan hash value: 241534218
------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1094 | 871K| | 1877K (1)| 00:01:14 |
| 1 | HASH GROUP BY | | 1094 | 871K| 4688K| 1877K (1)| 00:01:14 |
| 2 | NESTED LOOPS OUTER | | 5259 | 4190K| | 1877K (1)| 00:01:14 |
|* 3 | FILTER | | | | | | |
|* 4 | HASH JOIN RIGHT OUTER| | 5259 | 4139K| | 1866K (1)| 00:01:13 |
| 5 | TABLE ACCESS FULL | REP_MAPPER_SVC_FCO | 85 | 680 | | 3 (0)| 00:00:01 |
|* 6 | HASH JOIN RIGHT SEMI| | 5259 | 4098K| | 1866K (1)| 00:01:13 |
|* 7 | TABLE ACCESS FULL | REP_MAPPER_INTERFACE_ERROR | 33 | 363 | | 5 (0)| 00:00:01 |
|* 8 | TABLE ACCESS FULL | AUD_REQUEST_RESPONSE | 5259 | 4041K| | 1866K (1)| 00:01:13 |
|* 9 | INDEX UNIQUE SCAN | PER_ANBR_IDX | 1 | 10 | | 2 (0)| 00:00:01 |
------------------------------------------------------------------------------------------------------------------
通过使用json_table
EXPLAIN PLAN for
SELECT
jtresponse.xNumber as xNumber,
jtresponse.error_field as ERROR_FIELD,
replace(jtresponse.value_of_field_in_error, ',interfaceName=INTERFACES','') as VALUE_OF_FIELD_IN_ERROR,
jtresponse.error_description as ERROR_DESCRIPTION,
trim(arr.response.Status) as STATUS,
sf.sv_code as CENTER,
TO_CHAR(arr.created_date_time, 'YYYYMMDD' ) as DATE_OCCURANCE
from
aud_request_response arr,
person p,
rep_mapper_svc_fco sf,
rep_mapper_interface_error re,
json_table(response, '$'
COLUMNS (
nested path '$.ErrorRecord[*]' columns (
aNumber path '$.xNumber' null on error,
error_field path '$."error field"' null on error,
value_of_field_in_error path '$."value of field in error"' null on error,
error_description path '$."error description"' null on error
))) jtresponse
,json_table(request, '$'
COLUMNS (
nested path '$.DataRecord[*]' columns (
fileControl path '$.ACO' null on error
))) jtrequest
where jtrequest.fileControl =sf.fco_code(+)
and arr.request.interfaceName = 'CLAIMS'
and arr.request.interfaceName = re.interface_name
and jtresponse.xNumber = p.registration_number (+)
and arr.response.Status='Error'
and coalesce(sf.sv_code,'ATH') in('XS','YS','XZ','ZS','ASD')
GROUP BY
sv_code,
jtrequest.fileControl,
arr.request.interfaceName,
arr.response.Status,
jtresponse.error_field,
arr.created_date_time,
arr.updated_date_time,
jtresponse.value_of_field_in_error,
jtresponse.error_description,
jtresponse.xNumber;
SELECT * FROM table(DBMS_XPLAN.DISPLAY);
Plan hash value: 834586449
--------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
--------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 350G| 260T| | 1908M (2)| 20:42:27 |
| 1 | HASH GROUP BY | | 350G| 260T| 290T| 1908M (2)| 20:42:27 |
| 2 | NESTED LOOPS | | 350G| 260T| | 1168M (1)| 12:40:35 |
|* 3 | FILTER | | | | | | |
|* 4 | HASH JOIN RIGHT OUTER | | 42M| 32G| | 2009K (1)| 00:01:19 |
| 5 | TABLE ACCESS FULL | REP_MAPPER_SVC_FCO | 85 | 680 | | 3 (0)| 00:00:01 |
| 6 | NESTED LOOPS | | 42M| 32G| | 2009K (1)| 00:01:19 |
|* 7 | HASH JOIN RIGHT SEMI | | 5259 | 4098K| | 1866K (1)| 00:01:13 |
|* 8 | TABLE ACCESS FULL | REP_MAPPER_INTERFACE_ERROR | 33 | 363 | | 5 (0)| 00:00:01 |
|* 9 | TABLE ACCESS FULL | AUD_REQUEST_RESPONSE | 5259 | 4041K| | 1866K (1)| 00:01:13 |
| 10 | JSONTABLE EVALUATION | | | | | | |
| 11 | JSONTABLE EVALUATION | | | | | | |
--------------------------------------------------------------------------------------------------------------------
谢谢！
首先：两个查询不等价！
json_value 查询获取 DataRecord 和 ErrorRecord 数组中的第一个条目。使用 json_table 数据库为数组中的每个元素生成一行。
我发现 jtrequest 和 jtresponse 之间没有连接。所以查询正在生成这些数组的笛卡尔积。即，它为每个文档的第一个数组中的每个元素和第二个数组中的每个元素创建一行。
rows/bytes/time 列都是估计值。优化器根据 table 统计数据认为这是 rows/size data/query 持续时间。
计划中的第一行是（估计）查询 return。所以对于 json_table，它估计：
- 350G => 350 十亿 行
- 260T => 260 太字节 数据
- 20:42:27 => 20+ 小时 运行时间
由于多种原因，这些数字可能是错误的，但即使它们超过 1000 倍，您仍在查看大量数据。
我认为您需要弄清楚原始查询的目的 - 特别是它生成两个数组的笛卡尔积的原因。这会迅速增加数据量。