MaxCompute:EXPLAIN

The output results of the EXPLAIN statement include the following information:

• Dependencies between jobs

  For example, job0 is a root job. If a query requires only job0, only one row of data is displayed.

• Dependencies between tasks

  In Job job0:
  root Tasks: M1, M2
  J3_1_2_Stg1 depends on: M1, M2

  job0 contains the following tasks: M1, M2, and J3_1_2_Stg1. MaxCompute runs the J3_1_2_Stg1 task after the M1 and M2 tasks are run.

  Naming conventions of tasks:

  • MaxCompute provides four task types: map, reduce, join, and local work. The first letter in a task name indicates the type of the task. For example, M2Stg1 is a map task.

  • The digit that follows the first letter indicates the task ID. This ID is unique among all tasks that correspond to a specific query.

  • Digits separated by underscores (_) represent the direct dependency of a task. For example, J3_1_2_Stg1 indicates that the task with the ID of 3 depends on the M1 and M2 tasks.

• Dependencies between all operators in a task

  The operator string describes the execution semantics of a task. Operator string structure:

  In Task M2:
      Data source: mf_mc_bj.sale_detail_jt/sale_date=2013/region=china # Data source describes the input of the task. 
      TS: mf_mc_bj.sale_detail_jt/sale_date=2013/region=china           # TableScanOperator
          FIL: ISNOTNULL(customer_id)                                   # FilterOperator
              RS: order: +                                              # ReduceSinkOperator
                  nullDirection: *
                  optimizeOrderBy: False
                  valueDestLimit: 0
                  dist: HASH
                  keys:
                        customer_id
                  values:
                        customer_id (string)
                        total_price (double)
                  partitions:
                        customer_id
  
  
  In Task J3_1_2:
      JOIN:                                                           # JoinOperator
           StreamLineRead1 INNERJOIN StreamLineRead2
           keys:
               0:customer_id
               1:customer_id
  
          AGGREGATE: group by:customer_id                            # GroupByOperator
           UDAF: SUM(total_price) (__agg_0_sum)[Complete],SUM(total_price) (__agg_1_sum)[Complete]
              RS: order: +
                  nullDirection: *
                  optimizeOrderBy: True
                  valueDestLimit: 10
                  dist: HASH
                  keys:
                        customer_id
                  values:
                        customer_id (string)
                        __agg_0 (double)
                        __agg_1 (double)
                  partitions:
  
  
  In Task R4_3:
      SEL: customer_id,__agg_0,__agg_1                               # SelectOperator
          LIM:limit 10                                               # LimitOperator
              FS: output: Screen                                     # FileSinkOperator
                  schema:
                    customer_id (string) AS ashop
                    __agg_0 (double) AS ap
                    __agg_1 (double) AS bp

  Operator descriptions:

  • TableScanOperator (TS): describes the logic of FROM statement blocks in a query statement. The alias of the input table is displayed in the output results of the EXPLAIN statement.

  • SelectOperator (SEL): describes the logic of SELECT statement blocks in a query statement. The columns that are passed to the next operator are displayed in the execution results of the EXPLAIN statement. Multiple columns are separated by commas (,).

    • If a column is specified, the value is displayed in the <alias>.<column_name> format.

    • If an expression is specified, the value is displayed as a list of functions, such as func1(arg1_1, arg1_2, func2(arg2_1, arg2_2)).

    • If a constant is specified, the constant value is displayed.

  • FilterOperator (FIL): describes the logic of WHERE statement blocks in a query statement. The output results of the EXPLAIN statement include a WHERE expression, which is in a form that is similar to that of SelectOperator.

  • JoinOperator (JOIN): describes the logic of JOIN statement blocks in a query statement. The output results of the EXPLAIN statement show which tables are joined in which way.

  • GroupByOperator (AGGREGATE): describes the logic of aggregate operations. This operator is displayed if an aggregate function is used in a query statement. The content of the aggregate function is displayed in the execution results of the EXPLAIN statement.

  • ReduceSinkOperator (RS): describes the logic of data distribution between tasks. If the result of a task is transferred to another task, ReduceSinkOperator must be used to distribute data at the last stage of the task. The result sorting method, distributed keys, distributed values, and columns that are used to calculate the hash value are displayed in the output results of the EXPLAIN statement.

  • FileSinkOperator (FS): describes the logic of storage operations on final data records. If INSERT statement blocks are included in a query statement, the name of the table into which you want to insert data is displayed in the output results of the EXPLAIN statement.

  • LimitOperator (LIM): describes the logic of LIMIT statement blocks in a query statement. The number of returned rows that are specified in a LIMIT statement block is displayed in the execution results of the EXPLAIN statement.

  • MapjoinOperator (HASHJOIN): describes JOIN operations on large tables. This operator is similar to JoinOperator.

Sample source data is provided for you to better understand the examples in this topic. The following statements show how to create the sale_detail and sale_detail_jt tables and insert data into the tables.

-- Create two partitioned tables named sale_detail and sale_detail_jt. 
CREATE TABLE if NOT EXISTS sale_detail
(
shop_name     STRING,
customer_id   STRING,
total_price   DOUBLE
)
PARTITIONED BY (sale_date STRING, region STRING);

CREATE TABLE if NOT EXISTS sale_detail_jt
(
shop_name     STRING,
customer_id   STRING,
total_price   DOUBLE
)
PARTITIONED BY (sale_date STRING, region STRING);

-- Add partitions to the two tables. 
ALTER TABLE sale_detail ADD PARTITION (sale_date='2013', region='china') PARTITION (sale_date='2014', region='shanghai');
ALTER TABLE sale_detail_jt ADD PARTITION (sale_date='2013', region='china');

-- Insert data into the tables. 
INSERT INTO sale_detail PARTITION (sale_date='2013', region='china') VALUES ('s1','c1',100.1),('s2','c2',100.2),('s3','c3',100.3);
INSERT INTO sale_detail PARTITION (sale_date='2014', region='shanghai') VALUES ('null','c5',null),('s6','c6',100.4),('s7','c7',100.5);
INSERT INTO sale_detail_jt PARTITION (sale_date='2013', region='china') VALUES ('s1','c1',100.1),('s2','c2',100.2),('s5','c2',100.2);

-- Query data from the sale_detail and sale_detail_jt tables. Sample statements:
SET odps.sql.allow.fullscan=true;
SELECT * FROM sale_detail;
-- The following result is returned:
+------------+-------------+-------------+------------+------------+
| shop_name  | customer_id | total_price | sale_date  | region     |
+------------+-------------+-------------+------------+------------+
| s1         | c1          | 100.1       | 2013       | china      |
| s2         | c2          | 100.2       | 2013       | china      |
| s3         | c3          | 100.3       | 2013       | china      |
| null       | c5          | NULL        | 2014       | shanghai   |
| s6         | c6          | 100.4       | 2014       | shanghai   |
| s7         | c7          | 100.5       | 2014       | shanghai   |
+------------+-------------+-------------+------------+------------+

SET odps.sql.allow.fullscan=true;
SELECT * FROM sale_detail_jt;
-- The following result is returned:
+------------+-------------+-------------+------------+------------+
| shop_name  | customer_id | total_price | sale_date  | region     |
+------------+-------------+-------------+------------+------------+
| s1         | c1          | 100.1       | 2013       | china      |
| s2         | c2          | 100.2       | 2013       | china      |
| s5         | c2          | 100.2       | 2013       | china      |
+------------+-------------+-------------+------------+------------+

-- Create a table for the JOIN operation. 
SET odps.sql.allow.fullscan=true;
CREATE TABLE shop AS SELECT shop_name, customer_id, total_price FROM sale_detail;