Computing pricing

Subscription

After purchasing computing resources by using the subscription billing method, you can monitor and manage the resources in MaxCompute CU Management. For more information, see MaxCompute Management.

If you are a new user, we recommend that you select the pay-as-you-go billing method, where expenses are charged after computing jobs are completed based on the input data size. This is because you may use only a few resources when you use MaxCompute in the initial stage. If you purchase resources by using the subscription billing method, some resources may become idle. The pay-as-you-go billing method will charge lower expenses for new users who have fewer data requirements.

Pay-as-you-go for standard SQL jobs

For standard SQL jobs, expenses are charged after the jobs are completed based on the input data size. Each time you run a standard SQL job, MaxCompute calculates the expense based on the input data size and complexity of the job.

MaxCompute calculates the expense of each standard SQL job based on the input data size. The expenses calculated on the current day are collected at one time on the next day.

Expense of a standard SQL job = Input data size × SQL complexity × Unit price for standard SQL computing

• Input data size: the actual size of the data that an SQL statement scans. Most SQL statements support partition filtering and column pruning. Therefore, the input data size is generally much smaller than the size of the source table.
  • Column pruning: For example, if you submit the SQL statement select f1,f2,f3 from t1;, only the data in columns f1, f2, and f3 of table t1 is billed.
  • Partition filtering: For example, if you submit an SQL statement containing the WHERE clause where ds>"20130101", in which ds is the partition key column, only data in the partitions that is actually read is billed.
• SQL complexity: MaxCompute counts the keywords in SQL statements and then calculates the SQL complexity. The calculation details are as follows:
  • Number of keywords = Number of JOIN clauses + Number of GROUP BY clauses + Number of ORDER BY clauses + Number of DISTINCT clauses + Number of window functions + Max(Number of INSERT INTO clauses - 1, 1)
  • The relationship between the number of keywords in SQL statements and the SQL complexity is as follows:
    • If the number of keywords is less than or equal to 3, the SQL complexity is 1.
    • If the number of keywords is greater than 3 but less than or equal to 6, the SQL complexity is 1.5.
    • If the number of keywords is greater than 6 but less than or equal to 19, the SQL complexity is 2.
    • If the number of keywords is greater than or equal to 20, the SQL complexity is 4.

cost sql <SQL Sentence>;

odps@ $odps_project >cost sql SELECT DISTINCT total1 FROM
(SELECT id1, COUNT(f1) AS total1 FROM in1 GROUP BY id1) tmp1
ORDER BY total1 DESC LIMIT 100;
Intput:1825361100.8 Bytes
Complexity:1.5

1.7 × 1.5 × 0.0438 = USD 0.11

Pay-as-you-go for SQL jobs that process data in external tables

Expense of an SQL job that processes data in external tables = Input data size × Unit price for SQL computing that involves external tables

Pay-as-you-go for MapReduce jobs

Expense of a MapReduce job = Total billable hours × Unit price for MapReduce computing

Billable hours of a MapReduce job = Execution time in hours × Number of CPU cores that the job calls

For example, if you consume 100 CPU cores for running a MapReduce job for 0.5 hour, the billable hours you need to pay are calculated as follows: 0.5 × 100 = 50.

Pay-as-you-go for Spark jobs

Expense of a Spark job = Total billable hours × Unit price for Spark computing (USD 0.1041 per hour per job)

Billable hours of a Spark job = Max[Number of CPU cores × Execution time in hours, Ceiling(Memory size × Execution time in hours/4)]

For example, if you consume 2 CPU cores and 5 GB memory for running a Spark job for 1 hour, the billable hours you need to pay are calculated as follows: Max[2 × 1, Ceiling(5 × 1/4)] = 2. If you consume 2 CPU cores and 10 GB memory for running a Spark job for 1 hour, the billable hours you need to pay are calculated as follows: Max[2 × 1, Ceiling(10 × 1/4)] = 3.