[Maria-developers] Review for ANALYZE TABLE with Sampling
Hi Sergei! Can you review that you are happy with the storage engine API changes? I'veustructured the commit to be as small as possible to achieve the desired outcome. In my tests, we are now twice as fast as MySQL for a 10 mil row table with 13 columns. Vicențiu -------- Forwarded Message --------From: vicentiu@mariadb.orgTo: commits@mariadb.orgSubject: 53730224efd: Improve histogram collection performance by samplingDate: Sun, 10 Feb 2019 20:09:49 +0200 (EET) revision-id: 53730224efd987f97a6cc968ff5214ee499d84e0 (mariadb-10.4.1- 163-g53730224efd)parent(s): 3c305d3f1951f1667f84e48ddd98674c6318c39dauthor: Vicențiu Ciorbarucommitter: Vicențiu Ciorbarutimestamp: 2019-02-10 19:54:50 +0200message: Improve histogram collection performance by sampling Histogram collection is done by sampling a percentage of rows from the table,not looking at all individual ones. The default implementation, to keep the server's Engine IndepenentStatistics component working uses Bernoulli sampling. It does a simpletable scan, but only accepts rows that pass a dice roll. Thisimplementation is done as a storage engine interface method, so as toallow faster and/or more efficient implementations for storage enginesinternally. The number of rows collected is capped to a minimum of 50000 andincreases logarithmically with a coffecient of 4096. The coffecient ischosen so that we expect an error of less than 3% in our estimationsaccording to the paper:"Random Sampling for Histogram Construction: How much is enough?”– Surajit Chaudhuri, Rajeev Motwani, Vivek Narasayya, ACM SIGMOD, 1998. This interface is also a precursor to allowing SELECT ... FROM tablewith sampling to work. Performance wise, for a table of 10 million rows and 13 columns, 6 int,6 doubles, one string, the previous analyze table statistics took1 minute 20 seconds to collect all data. Post implementation, thetime is less than 6 seconds. This was run on an InnoDB table, NVME SSD withapproximately 2GB/s read speed and 500MB/s write speed. --- mysql-test/main/selectivity.result | 8 +++---- mysql- test/main/selectivity_innodb.result | 8 +++-- -- sql/handler.cc | 14 +++++++++++ sql/handler.h | 40 ++++++++++++++++++++++++++++++- sql/sql_statistics.cc | 32 +++++++++++++++++++------ 5 files changed, 86 insertions(+), 16 deletions(-) diff --git a/mysql-test/main/selectivity.result b/mysql- test/main/selectivity.resultindex 00907235ecc..6d09c1c9b62 100644--- a/mysql-test/main/selectivity.result+++ b/mysql- test/main/selectivity.result@@ -1290,9 +1290,9 @@ explain extended select * from t1, t2, t1 as t3 where t1.b=t2.c and t2.d=t3.a and t3.b<5 and t1.a < 2000; id select_type table type possibl e_keys key key_len ref rows filtered Extra-1 SIMPLE t1 ALL NULL NULL NULL NULL 262144 100.00 Using where+1 SIMPLE t1 ALL NULL NULL NULL NULL 262117 100.00 Using where 1 SIMPLE t2 ref c,d c 5 test.t1.b 5 100.00 -1 SIMPLE t3 ALL NULL NULL NULL NULL 262144 100.00 Using where; Using join buffer (flat, BNL join)+1 SIMPLE t3 ALL NULL NULL NULL NULL 262117 100.00 Using where; Using join buffer (flat, BNL join) Warnings: Note 1003 select `test`.`t1`.`a` AS `a`,`test`.`t1`.`b` AS `b`,`test`.`t2`.`c` AS `c`,`test`.`t2`.`d` AS `d`,`test`.`t3`.`a` AS `a`,`test`.`t3`.`b` AS `b` from `test`.`t1` join `test`.`t2` join `test`.`t1` `t3` where `test`.`t2`.`c` = `test`.`t1`.`b` and `test`.`t3`.`a` = `test`.`t2`.`d` and `test`.`t3`.`b` < 5 and `test`.`t1`.`a` < 2000 select * from t1, t2, t1 as t3@@ -1307,9 +1307,9 @@ explain extended select * from t1, t2, t1 as t3 where t1.b=t2.c and t2.d=t3.a and t3.b<5 and t1.a < 2000; id select_ type table type possible_keys key key_len ref rows filtered Extra-1 SIMPLE t3 ALL NULL NULL NULL NULL 262144 0.00 Using where+1 SIMPLE t3 ALL NULL NULL NULL NULL 262117 0.00 Using where 1 SIMPLE t2 ref c,d d 5 test.t3.a 7 100.00 -1 SIMPLE t1 ALL NULL NULL NULL NULL 262144 2.00 Using where; Using join buffer (flat, BNL join)+1 SIMPLE t1 ALL NULL NULL NULL NULL 262117 2.00 Using where; Using join buffer (flat, BNL join) Warnings: Note 1003 select `test`.`t1`.`a` AS `a`,`test`.`t1`.`b` AS `b`,`test`.`t2`.`c` AS `c`,`test`.`t2`.`d` AS `d`,`test`.`t3`.`a` AS `a`,`test`.`t3`.`b` AS `b` from `test`.`t1` join `test`.`t2` join `test`.`t1` `t3` where `test`.`t1`.`b` = `test`.`t2`.`c` and `test`.`t2`.`d` = `test`.`t3`.`a` and `test`.`t3`.`b` < 5 and `test`.`t1`.`a` < 2000 select * from t1, t2, t1 as t3diff --git a/mysql-test/main/selectivity_innodb.result b/mysql-test/main/selectivity_innodb.resultindex 93917065722..0b20a40f69f 100644--- a/mysql- test/main/selectivity_innodb.result+++ b/mysql- test/main/selectivity_innodb.result@@ -1300,9 +1300,9 @@ explain extended select * from t1, t2, t1 as t3 where t1.b=t2.c and t2.d=t3.a and t3.b<5 and t1.a < 2000; id select_type table type possibl e_keys key key_len ref rows filtered Extra-1 SIMPLE t1 ALL NULL NULL NULL NULL 262144 100.00 Using where+1 SIMPLE t1 ALL NULL NULL NULL NULL 262117 100.00 Using where 1 SIMPLE t2 ref c,d c 5 test.t1.b 5 100.00 -1 SIMPLE t3 ALL NULL NULL NULL NULL 262144 100.00 Using where; Using join buffer (flat, BNL join)+1 SIMPLE t3 ALL NULL NULL NULL NULL 262117 100.00 Using where; Using join buffer (flat, BNL join) Warnings: Note 1003 select `test`.`t1`.`a` AS `a`,`test`.`t1`.`b` AS `b`,`test`.`t2`.`c` AS `c`,`test`.`t2`.`d` AS `d`,`test`.`t3`.`a` AS `a`,`test`.`t3`.`b` AS `b` from `test`.`t1` join `test`.`t2` join `test`.`t1` `t3` where `test`.`t2`.`c` = `test`.`t1`.`b` and `test`.`t3`.`a` = `test`.`t2`.`d` and `test`.`t3`.`b` < 5 and `test`.`t1`.`a` < 2000 select * from t1, t2, t1 as t3@@ -1317,9 +1317,9 @@ explain extended select * from t1, t2, t1 as t3 where t1.b=t2.c and t2.d=t3.a and t3.b<5 and t1.a < 2000; id select_ type table type possible_keys key key_len ref rows filtered Extra-1 SIMPLE t3 ALL NULL NULL NULL NULL 262144 0.00 Using where+1 SIMPLE t3 ALL NULL NULL NULL NULL 262117 0.00 Using where 1 SIMPLE t2 ref c,d d 5 test.t3.a 7 100.00 -1 SIMPLE t1 ALL NULL NULL NULL NULL 262144 2.00 Using where; Using join buffer (flat, BNL join)+1 SIMPLE t1 ALL NULL NULL NULL NULL 262117 2.00 Using where; Using join buffer (flat, BNL join) Warnings: Note 1003 select `test`.`t1`.`a` AS `a`,`test`.`t1`.`b` AS `b`,`test`.`t2`.`c` AS `c`,`test`.`t2`.`d` AS `d`,`test`.`t3`.`a` AS `a`,`test`.`t3`.`b` AS `b` from `test`.`t1` join `test`.`t2` join `test`.`t1` `t3` where `test`.`t1`.`b` = `test`.`t2`.`c` and `test`.`t2`.`d` = `test`.`t3`.`a` and `test`.`t3`.`b` < 5 and `test`.`t1`.`a` < 2000 select * from t1, t2, t1 as t3diff --git a/sql/handler.cc b/sql/handler.ccindex 2e45b5883ea..16fb126918e 100644--- a/sql/handler.cc+++ b/sql/handler.cc@@ -7547,3 +7547,17 @@ bool Vers_parse_info::check_sys_fields(const Lex_table_name &table_name, "ROW END" : found_flag ? "ROW START" : "ROW START/END"); return true; }++int handler::random_sample(uchar *buf)+{+ int rc;+ THD *thd= ha_thd();+ do+ {+ if (table->in_use-
check_killed(1))+ return HA_ERR_ABORTED_BY_USER;+ rc= rnd_next(buf);+ } while (rc == HA_ERR_RECORD_DELETED || thd_rnd(thd) > sample_fraction);++ return rc;+}diff --git a/sql/handler.h b/sql/handler.hindex dfb2333b24e..fcdadbeb42b 100644--- a/sql/handler.h+++ b/sql/handler.h@@ -1913,6 +1913,11 @@ enum enum_stats_auto_recalc { HA_STATS_AUTO_RECALC_DEFAULT= 0, HA_STATS_AUTO_RECALC_ON, HA_STATS_AUTO_RECALC_OFF }; +enum sample_mode {+ HA_SAMPLE_BERNOULLI= 0,+ HA_SAMPLE_SYSTEM+};+ /** A helper struct for schema DDL statements: CREATE SCHEMA [IF NOT EXISTS] name [ schema_specification... ]@@ -2947,9 +2952,11 @@ class handler :public Sql_alloc /** Length of ref (1-8 or the clustered key length) */ uint ref_length; FT_INFO *ft_handler;- enum init_stat { NONE=0, INDEX, RND };+ enum init_stat { NONE=0, INDEX, RND, SAMPLE }; init_stat inited, pre_inited; + double sample_fraction= 0;+ enum sample_mode sample_mode; const COND *pushed_cond; /** next_insert_id is the next value which should be inserted into the@@ -3112,6 +3119,31 @@ class handler :public Sql_alloc virtual int prepare_range_scan(const key_range *start_key, const key_range *end_key) { return 0; } + int ha_random_sample_init(THD *thd, enum sample_mode mode, double fraction)+ __attribute__((warn_unused_result))+ {+ DBUG_ENTER("h a_random_sample_init");+ DBUG_ASSERT(inited==NONE);+ int result;+ sample_mode= mode;+ sample_fraction= fraction;+ inited= (result= random_sample_init(mode, fraction)) ? NONE : SAMPLE;+ DBUG_RETURN(result);+ }+ int ha_random_sample(uchar *buf)+ __attribute__((warn_unused_result))+ {+ DBUG_ENTER("ha_ra ndom_sample");+ DBUG_ASSERT(inited == SAMPLE);+ DBUG_RETURN(random_sample(buf));+ }+ int ha_random_sample_end()+ {+ DBUG_ENTER("ha_random_sample_end");+ inited= NONE;+ DBUG_RETURN(random_sample_end());+ }+ int ha_rnd_init(bool scan) __attribute__ ((warn_unused_result)) { DBUG_EXECUTE_IF("ha_rnd_init_fail", return HA_ERR_TABLE_DEF_CHANGED;);@@ -4425,6 +4457,12 @@ class handler :public Sql_alloc /* Note: ha_index_read_idx_map() may bypass index_init() */ virtual int index_init(uint idx, bool sorted) { return 0; } virtual int index_end() { return 0; }+ virtual int random_sample_init(enum sample_mode mode, double fraction)+ {+ return rnd_init(TRUE);+ }+ virtual int random_sample(uchar *buf);+ virtual int random_sample_end() { return rnd_end(); } /** rnd_init() can be called two times without rnd_end() in between (it only makes sense if scan=1).diff --git a/sql/sql_statistics.cc b/sql/sql_statistics.ccindex db214a1fe28..22a015821de 100644--- a/sql/sql_statistics.cc+++ b/sql/sql_statistics.cc@@ -2727,12 +2727,16 @@ int
collect_statistics_for_table(THD *thd, TABLE *table) Field *table_field; ha_rows rows= 0; handler *file=table->file;+ double sample_fraction;+ const ha_rows MIN_THRESHOLD_FOR_SAMPLING= 50000; DBUG_ENTER("collect_statistics_for_table"); table- >collected_stats->cardinality_is_null= TRUE; table->collected_stats- >cardinality= 0; + table->file->info(HA_STATUS_VARIABLE);+ for (field_ptr= table->field; *field_ptr; field_ptr++) { table_field= *field_ptr; @@ -2743,12 +2747,27 @@ int collect_statistics_for_table(THD *thd, TABLE *table) restore_record(table, s->default_values); - /* Perform a full table scan to collect statistics on 'table's columns */- if (!(rc= file->ha_rnd_init(TRUE)))- { ++ if (file->records() < MIN_THRESHOLD_FOR_SAMPLING)+ {+ sample_fraction= 1;+ }+ else+ {+ sample_fraction= std::fmin(+ (MIN_THRESHOLD_FOR_SAMPLING + 4096 *+ log(200 * file->records())) / file->records(), 1);+ }+++ /* Fetch samples from the table to collect statistics on table's columns */++ if (!(rc= file->ha_random_sample_init(thd, HA_SAMPLE_BERNOULLI,+ sample_fra ction)))+ { DEBUG_SYNC(table->in_use, "statistics_collection_start"); - while ((rc= file- >ha_rnd_next(table->record[0])) != HA_ERR_END_OF_FILE)+ while ((rc= file->ha_random_sample(table->record[0])) != HA_ERR_END_OF_FILE) { if (thd->killed) break;@@ -2768,10 +2787,9 @@ int collect_statistics_for_table(THD *thd, TABLE *table) break; rows++; }- file- >ha_rnd_end();+ file->ha_random_sample_end(); } rc= (rc == HA_ERR_END_OF_FILE && !thd->killed) ? 0 : 1;- /* Calculate values for all statistical characteristics on columns and and for each field f of 'table' save them in the write_stat structure@@ -2780,7 +2798,7 @@ int collect_statistics_for_table(THD *thd, TABLE *table) if (!rc) { table->collected_stats->cardinality_is_null= FALSE;- table->collected_stats->cardinality= rows;+ table- >collected_stats->cardinality= rows / sample_fraction; } bitmap_clear_all(table->write_set);
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Vicențiu Ciorbaru