[Bug]Fix some schema change not work right
This CL mainly fix some schema change to varchar type not work right
because forget to logic check && Add ConvertTypeResolver to add
supported convert type in order to avoid forget logic check
This CL mainly changes:
1. Reorganized the code logic to limit the supported json format to two, and the import behavior is more consistent.
2. Modified the statistical behavior of the number of error rows when loading in json format, so that the error rows can be counted correctly.
3. See `load-json-format.md` to get details of loading json format.
Currently we choose BE random without check disk is available,
the create table will failed until create tablet task is sent to BE
and BE will check is there has available capacity to create tablet.
So check backend disk available by storage medium will reduce unnecessary RPC call.
1. User interface:
1.1 Spark resource management
Spark is used as an external computing resource in Doris to do ETL work. In the future, there may be other external resources that will be used in Doris, for example, MapReduce is used for ETL, Spark/GPU is used for queries, HDFS/S3 is used for external storage. We introduced resource management to manage these external resources used by Doris.
```sql
-- create spark resource
CREATE EXTERNAL RESOURCE resource_name
PROPERTIES
(
type = spark,
spark_conf_key = spark_conf_value,
working_dir = path,
broker = broker_name,
broker.property_key = property_value
)
-- drop spark resource
DROP RESOURCE resource_name
-- show resources
SHOW RESOURCES
SHOW PROC "/resources"
-- privileges
GRANT USAGE_PRIV ON RESOURCE resource_name TO user_identity
GRANT USAGE_PRIV ON RESOURCE resource_name TO ROLE role_name
REVOKE USAGE_PRIV ON RESOURCE resource_name FROM user_identity
REVOKE USAGE_PRIV ON RESOURCE resource_name FROM ROLE role_name
```
- CREATE EXTERNAL RESOURCE:
FOR user_name is optional. If there has, the external resource belongs to this user. If not, the external resource belongs to the system and all users are available.
PROPERTIES：
1. type: resource type. Only support spark now.
2. spark configuration: follow the standard writing of Spark configurations, refer to: https://spark.apache.org/docs/latest/configuration.html.
3. working_dir: optional, used to store ETL intermediate results in spark ETL.
4. broker: optional, used in spark ETL. The ETL intermediate results need to be read with the broker when pushed into BE.
Example:
```sql
CREATE EXTERNAL RESOURCE "spark0"
PROPERTIES
(
"type" = "spark",
"spark.master" = "yarn",
"spark.submit.deployMode" = "cluster",
"spark.jars" = "xxx.jar,yyy.jar",
"spark.files" = "/tmp/aaa,/tmp/bbb",
"spark.yarn.queue" = "queue0",
"spark.executor.memory" = "1g",
"spark.hadoop.yarn.resourcemanager.address" = "127.0.0.1:9999",
"spark.hadoop.fs.defaultFS" = "hdfs://127.0.0.1:10000",
"working_dir" = "hdfs://127.0.0.1:10000/tmp/doris",
"broker" = "broker0",
"broker.username" = "user0",
"broker.password" = "password0"
)
```
- SHOW RESOURCES:
General users can only see their own resources.
Admin and root users can show all resources.
1.2 Create spark load job
```sql
LOAD LABEL db_name.label_name
(
DATA INFILE ("/tmp/file1") INTO TABLE table_name, ...
)
WITH RESOURCE resource_name
[(key1 = value1, ...)]
[PROPERTIES (key2 = value2, ... )]
```
Example:
```sql
LOAD LABEL example_db.test_label
(
DATA INFILE ("hdfs:/127.0.0.1:10000/tmp/file1") INTO TABLE example_table
)
WITH RESOURCE "spark0"
(
"spark.executor.memory" = "1g",
"spark.files" = "/tmp/aaa,/tmp/bbb"
)
PROPERTIES ("timeout" = "3600")
```
The spark configurations in load stmt can override the existing configuration in the resource for temporary use.
#3010
