Raajay,
You don't have col stats hence it assumes 1 for row count.
What version of Hive are you on?
Thanks
John
From: Raajay <raaja...@gmail.com<mailto:raaja...@gmail.com>>
Reply-To: "u...@hive.apache.org<mailto:u...@hive.apache.org>"
<u...@hive.apache.org<mailto:u...@hive.apache.org>>
Date: Monday, August 24, 2015 at 5:19 PM
To: "u...@hive.apache.org<mailto:u...@hive.apache.org>"
<u...@hive.apache.org<mailto:u...@hive.apache.org>>
Cc: "dev@hive.apache.org<mailto:dev@hive.apache.org>"
<dev@hive.apache.org<mailto:dev@hive.apache.org>>
Subject: CBO - get cost of the plan
Hello,
I am interested to get the cost of the query plans as calculated by the CBO.
How can I get that information ? For example, consider a query with a three way
join of the following form:
Query
=====
insert overwrite table output_tab
select
a_day, a_product, b_alternate, (a_sales + b_sales + c_sales) as total_sales
from
tableA a join tableB b
on a.a_day = b.b_day and a.a_product = b.b_product
join tableC c
on b.b_day = c.c_day and b.b_alternate = c.c_alternate;
The number of rows for tableA, tableB, and tableC are of the order of 10000. I
believe, that by "analyzing columns" of all the tables Hive will have
statistics regarding the number of rows, distinct values, etc. However, when I
try to print out the operator tree as determined by the CalcitePlanner, I get
the following output.
Print out of the Operator Tree
======================
HiveProject(a_day=[$4], a_product=[$5], b_alternate=[$2], total_sales=[+(+($6,
$3), $9)]): rowcount = 1.0, cumulative cost = {4.0 rows, 0.0 cpu, 0.0 io}, id =
150
HiveJoin(condition=[AND(=($0, $7), =($2, $8))], joinType=[inner],
algorithm=[none], cost=[{2.0 rows, 0.0 cpu, 0.0 io}]): rowcount = 1.0,
cumulative cost = {4.0 rows, 0.0 cpu, 0.0 io}, id = 148
HiveJoin(condition=[AND(=($4, $0), =($5, $1))], joinType=[inner],
algorithm=[none], cost=[{2.0 rows, 0.0 cpu, 0.0 io}]): rowcount = 1.0,
cumulative cost = {2.0 rows, 0.0 cpu, 0.0 io}, id = 143
HiveProject(b_day=[$0], b_product=[$1], b_alternate=[$2], b_sales=[$3]):
rowcount = 1.0, cumulative cost = {0.0 rows, 0.0 cpu, 0.0 io}, id = 138
HiveTableScan(table=[[default.tableb]]): rowcount = 1.0, cumulative
cost = {0}, id = 44
HiveProject(a_day=[$0], a_product=[$1], a_sales=[$3]): rowcount = 1.0,
cumulative cost = {0.0 rows, 0.0 cpu, 0.0 io}, id = 141
HiveTableScan(table=[[default.tablea]]): rowcount = 1.0, cumulative
cost = {0}, id = 42
HiveProject(c_day=[$0], c_alternate=[$2], c_sales=[$3]): rowcount = 1.0,
cumulative cost = {0.0 rows, 0.0 cpu, 0.0 io}, id = 146
HiveTableScan(table=[[default.tablec]]): rowcount = 1.0, cumulative cost
= {0}, id = 47
The number of rows as displayed here is 1.0, which is clearly not the correct
value.
- Raajay.
