Andrés Taylor systay

Query Analysis Report

Date of Analysis: 2024-01-01 01:02:03
Analyzed File: testdata/keys-log.json

File analyzed: go/summarize/testdata/keys-log.json

	{
	infSchema := map[string]map[string]query.Type{}
	cols := map[string]query.Type{}
	cols["USER"] = query.Type(6165)
	cols["HOST"] = query.Type(6165)
	cols["GRANTEE"] = query.Type(6165)
	cols["GRANTEE_HOST"] = query.Type(6165)
	cols["ROLE_NAME"] = query.Type(6165)
	cols["ROLE_HOST"] = query.Type(6165)
	cols["IS_GRANTABLE"] = query.Type(6165)

	SELECT O_YEAR, SUM(CASE WHEN NATION = 'BRAZIL' THEN VOLUME ELSE 0 END)/SUM(VOLUME) AS MKT_SHARE
	FROM (SELECT datepart(yy,O_ORDERDATE) AS O_YEAR, L_EXTENDEDPRICE*(1-L_DISCOUNT) AS VOLUME, N2.N_NAME AS NATION
	FROM PART, SUPPLIER, LINEITEM, ORDERS, CUSTOMER, NATION N1, NATION N2, REGION
	WHERE P_PARTKEY = L_PARTKEY AND S_SUPPKEY = L_SUPPKEY AND L_ORDERKEY = O_ORDERKEY
	AND O_CUSTKEY = C_CUSTKEY AND C_NATIONKEY = N1.N_NATIONKEY AND
	N1.N_REGIONKEY = R_REGIONKEY AND R_NAME = 'AMERICA' AND S_NATIONKEY = N2.N_NATIONKEY
	AND O_ORDERDATE BETWEEN '1995-01-01' AND '1996-12-31' AND P_TYPE= 'ECONOMY ANODIZED STEEL') AS ALL_NATIONS
	GROUP BY O_YEAR
	ORDER BY O_YEAR

	\| -> Table scan on <temporary> (actual time=0.001..0.002 rows=8 loops=1)
	-> Aggregate using temporary table (actual time=0.635..0.637 rows=8 loops=1)
	-> Nested loop left join (actual time=0.382..0.555 rows=8 loops=1)
	-> Nested loop left join (actual time=0.375..0.532 rows=8 loops=1)
	-> Nested loop left join (actual time=0.373..0.526 rows=8 loops=1)
	-> Nested loop inner join (actual time=0.367..0.513 rows=8 loops=1)
	-> Inner hash join (no condition) (actual time=0.207..0.218 rows=13 loops=1)
	-> Table scan on i (cost=0.00 rows=0) (actual time=0.001..0.005 rows=13 loops=1)
	-> Fill information schema table i (actual time=0.172..0.177 rows=13 loops=1)
	-> Hash

	--- FAIL: TestMultipleUpdatesFromDifferentShards/3 (0.04s)
	uptate_controller_test.go:170:
	Error Trace: uptate_controller_test.go:170
	Error: Not equal:
	expected: 2
	actual : 1
	Test: TestMultipleUpdatesFromDifferentShards/3
	Messages: signal required
	uptate_controller_test.go:172:
	Error Trace: uptate_controller_test.go:172

	2024-06-04T06:01:03.093029Z 8 Connect root@localhost on using TCP/IP
	2024-06-04T06:01:03.094962Z 8 Query /* mysql-connector-java-8.0.30 (Revision: 1de2fe873fe26189564c030a343885011412976a) */SELECT @@session.auto_increment_increment AS auto_increment_increment, @@character_set_client AS character_set_client, @@character_set_connection AS character_set_connection, @@character_set_results AS character_set_results, @@character_set_server AS character_set_server, @@collation_server AS collation_server, @@collation_connection AS collation_connection, @@init_connect AS init_connect, @@interactive_timeout AS interactive_timeout, @@license AS license, @@lower_case_table_names AS lower_case_table_names, @@max_allowed_packet AS max_allowed_packet, @@net_write_timeout AS net_write_timeout, @@performance_schema AS performance_schema, @@sql_mode AS sql_mode, @@system_time_zone AS system_time_zone, @@time_zone AS time_zone, @@transaction_isolation AS transaction_isolation, @@wait_timeout AS wait_timeout
	2024-06-0

	Traditional query optimizing is mostly about two things: in which order and from where to access data, and how to then combine it so it answers the query that the user wrote.

	You have problably seen the tree shapes execution plans that are produced from query planning. I'll use an example from the MySQL docs:

	mysql> EXPLAIN FORMAT=TREE
	-> SELECT *
	-> FROM t1
	-> JOIN t2
	-> ON (t1.c1 = t2.c1 AND t1.c2 < t2.c2)
	-> JOIN t3