Case: Setting Partial Cluster Keys

You can add PARTIAL CLUSTER KEY(column_name[,...]) to the definition of a column-store table to set one or more columns of this table as partial cluster keys. In this way, each 70 CUs (4.2 million rows) will be sorted based on the cluster keys by default during data import and the value range is narrowed down for each of the new 70 CUs. If the where condition in the query statement contains these columns, the filtering performance will be improved.

Use partial cluster keys.

     
      
        
        
          CREATE TABLE lineitem
(
L_ORDERKEY    BIGINT NOT NULL
, L_PARTKEY     BIGINT NOT NULL
, L_SUPPKEY     BIGINT NOT NULL
, L_LINENUMBER  BIGINT NOT NULL
, L_QUANTITY    DECIMAL(15,2) NOT NULL
, L_EXTENDEDPRICE  DECIMAL(15,2) NOT NULL
, L_DISCOUNT    DECIMAL(15,2) NOT NULL
, L_TAX         DECIMAL(15,2) NOT NULL
, L_RETURNFLAG  CHAR(1) NOT NULL
, L_LINESTATUS  CHAR(1) NOT NULL
, L_SHIPDATE    DATE NOT NULL
, L_COMMITDATE  DATE NOT NULL
, L_RECEIPTDATE DATE NOT NULL
, L_SHIPINSTRUCT CHAR(25) NOT NULL
, L_SHIPMODE     CHAR(10) NOT NULL
, L_COMMENT      VARCHAR(44) NOT NULL
)
with (orientation = column)
distribute by hash(L_ORDERKEY);

select
sum(l_extendedprice * l_discount) as revenue
from
lineitem
where
l_shipdate >= '1994-01-01'::date
and l_shipdate < '1994-01-01'::date + interval '1 year'
and l_discount between 0.06 - 0.01 and 0.06 + 0.01
and l_quantity < 24;

         

       

     
    

In the where condition, both the l_shipdate and l_quantity columns have a few distinct values, and their values can be used for min/max filtering. Therefore, modify the table definition as follows:

     
      
        
        
          CREATE TABLE lineitem
(
L_ORDERKEY    BIGINT NOT NULL
, L_PARTKEY     BIGINT NOT NULL
, L_SUPPKEY     BIGINT NOT NULL
, L_LINENUMBER  BIGINT NOT NULL
, L_QUANTITY    DECIMAL(15,2) NOT NULL
, L_EXTENDEDPRICE  DECIMAL(15,2) NOT NULL
, L_DISCOUNT    DECIMAL(15,2) NOT NULL
, L_TAX         DECIMAL(15,2) NOT NULL
, L_RETURNFLAG  CHAR(1) NOT NULL
, L_LINESTATUS  CHAR(1) NOT NULL
, L_SHIPDATE    DATE NOT NULL
, L_COMMITDATE  DATE NOT NULL
, L_RECEIPTDATE DATE NOT NULL
, L_SHIPINSTRUCT CHAR(25) NOT NULL
, L_SHIPMODE     CHAR(10) NOT NULL
, L_COMMENT      VARCHAR(44) NOT NULL
, partial cluster key(l_shipdate, l_quantity)
)
with (orientation = column)
distribute by hash(L_ORDERKEY);

         

       

     
    

Import the data again and run the query statement. Then, compare the execution time before and after partial cluster keys are used.

Figure 1 Partial cluster keys not used

Figure 2 CU loading without partial cluster keys

Figure 3 Partial cluster keys used

Figure 4 CU loading with partial cluster keys

After partial cluster keys are used, the execution time of 5-- CStore Scan on public.lineitem decreases by 1.2s because 84 CUs are filtered out.

Select partial cluster keys.
- The following data types support cluster keys: character varying(n), varchar(n), character(n), char(n), text, nvarchar2, timestamp with time zone, timestamp without time zone, date, time without time zone, and time with time zone.
- Smaller number of distinct values in a partial cluster key generates higher filtering performance.
- Columns that can filter out larger amount of data is preferentially selected as partial cluster keys.
- If multiple columns are selected as partial cluster keys, the columns are used in sequence to sort data. You are advised to select a maximum of three columns.
Modify parameters to reduce the impact of partial cluster keys on the import performance.
After partial cluster keys are used, data will be sorted when they are imported, affecting the import performance. If all the data can be sorted in the memory, the keys have little impact on import. If some data cannot be sorted in the memory and is written into a temporary file for sorting, the import performance will be greatly affected.

The memory used for sorting is specified by the psort_work_mem parameter. You can set it to a larger value so that the sorting has less impact on the import performance.

The volume of data to be sorted is specified by the PARTIAL_CLUSTER_ROWS parameter of the table. Decreasing the value of this parameter reduces the amount of data to be sorted at a time. PARTIAL_CLUSTER_ROWS is usually used along with the MAX_BATCHROW parameter. The value of PARTIAL_CLUSTER_ROWS must be an integer multiple of the MAX_BATCHROW value. MAX_BATCHROW specifies the maximum number of rows in a CU.