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Commit 2a1cdbab authored by Sergei Petrunia's avatar Sergei Petrunia
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Fix JSON parsing: future-proof data representation in JSON, code cleanup

parent a0b4a868
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Showing with 1349 additions and 1288 deletions
include/json_lib.h
View file @ 2a1cdbab
......@@ -283,12 +283,13 @@ int json_key_matches(json_engine_t *je, json_string_t *k);
int json_read_value(json_engine_t *j);
/*
* json_smart_read_value() reads parses a scalar value and value length from the json engine,
* and copies them into `value` and `value_length` respectively.
* It should only be called when the json_engine state is JST_VALUE.
* If it encounters a non-scalar value (say object or array) before getting to value_len,
* such value is also read and copied into value.
*/
json_smart_read_value() reads a JSON value. Pointer to value is stored in
*value and its length in *value_len.
if the value is non a scalar, it returns pointers to its JSON
representation.
The function should only be called when je->state==JST_VALUE.
*/
enum json_types json_smart_read_value(json_engine_t *je, const char **value, int *value_len);
/*
......
mysql-test/main/statistics_json.result
View file @ 2a1cdbab
......@@ -232,12 +232,12 @@ nulls_ratio, avg_frequency,
hist_size, hist_type, HEX(histogram)
FROM mysql.column_stats;
db_name table_name column_name min_value max_value nulls_ratio avg_frequency hist_size hist_type HEX(histogram)
test t1 a 0 49 0.0000 1.0000 4 JSON_HB 5B0A20202239222C0A2020223139222C0A2020223331222C0A2020223430220A5D
test t1 b vvvvvvvvvvvvv zzzzzzzzzzzzzzzzzz 0.2000 6.4000 4 JSON_HB 5B0A20202276767676767676767676767676222C0A20202277777777777777777777777777777777777777777777777777777777222C0A202022797979222C0A2020227A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A220A5D
test t1 c aaaa dddddddd 0.1250 7.0000 4 JSON_HB 5B0A20202261616161222C0A202022626262626262222C0A202022636363636363636363222C0A2020226464646464646464220A5D
test t1 d 1989-03-12 1999-07-23 0.1500 8.5000 4 JSON_HB 5B0A202022313938392D30332D3132222C0A202022313939302D30352D3135222C0A202022313939302D30352D3135222C0A202022313939392D30372D3233220A5D
test t1 e 0.01 0.112 0.2250 6.2000 4 JSON_HB 5B0A202022302E3031222C0A202022302E303132222C0A202022302E3035222C0A202022302E31220A5D
test t1 f 1 5 0.2000 6.4000 4 JSON_HB 5B0A20202202222C0A20202203222C0A20202204222C0A20202204220A5D
test t1 a 0 49 0.0000 1.0000 4 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B2239222C20223139222C20223331222C20223430225D0A7D
test t1 b vvvvvvvvvvvvv zzzzzzzzzzzzzzzzzz 0.2000 6.4000 4 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B0A202020202276767676767676767676767676222C0A202020202277777777777777777777777777777777777777777777777777777777222C0A2020202022797979222C0A20202020227A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A220A20205D0A7D
test t1 c aaaa dddddddd 0.1250 7.0000 4 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B2261616161222C2022626262626262222C2022636363636363636363222C20226464646464646464225D0A7D
test t1 d 1989-03-12 1999-07-23 0.1500 8.5000 4 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B22313938392D30332D3132222C2022313939302D30352D3135222C2022313939302D30352D3135222C2022313939392D30372D3233225D0A7D
test t1 e 0.01 0.112 0.2250 6.2000 4 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B22302E3031222C2022302E303132222C2022302E3035222C2022302E31225D0A7D
test t1 f 1 5 0.2000 6.4000 4 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B2202222C202203222C202204222C202204225D0A7D
DELETE FROM mysql.column_stats;
set histogram_size=8;
set histogram_type=@DOUBLE_PREC_TYPE;
......@@ -251,12 +251,12 @@ nulls_ratio, avg_frequency,
hist_size, hist_type, HEX(histogram)
FROM mysql.column_stats;
db_name table_name column_name min_value max_value nulls_ratio avg_frequency hist_size hist_type HEX(histogram)
test t1 a 0 49 0.0000 1.0000 8 JSON_HB 5B0A20202234222C0A20202239222C0A2020223135222C0A2020223231222C0A2020223239222C0A2020223333222C0A2020223339222C0A2020223433220A5D
test t1 b vvvvvvvvvvvvv zzzzzzzzzzzzzzzzzz 0.2000 6.4000 8 JSON_HB 5B0A20202276767676767676767676767676222C0A20202276767676767676767676767676222C0A20202277777777777777777777777777777777777777777777777777777777222C0A20202277777777777777777777777777777777777777777777777777777777222C0A2020227878787878787878787878787878787878787878787878787878222C0A202022797979222C0A202022797979222C0A2020227A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A220A5D
test t1 c aaaa dddddddd 0.1250 7.0000 8 JSON_HB 5B0A20202261616161222C0A20202261616161222C0A202022626262626262222C0A202022626262626262222C0A202022636363636363636363222C0A202022636363636363636363222C0A2020226464646464646464222C0A2020226464646464646464220A5D
test t1 d 1989-03-12 1999-07-23 0.1500 8.5000 8 JSON_HB 5B0A202022313938392D30332D3132222C0A202022313938392D30332D3132222C0A202022313939302D30352D3135222C0A202022313939302D30352D3135222C0A202022313939302D30352D3135222C0A202022313939302D30352D3135222C0A202022313939392D30372D3233222C0A202022313939392D30372D3233220A5D
test t1 e 0.01 0.112 0.2250 6.2000 8 JSON_HB 5B0A202022302E3031222C0A202022302E3031222C0A202022302E3031222C0A202022302E303132222C0A202022302E3035222C0A202022302E31222C0A202022302E31222C0A202022302E313132220A5D
test t1 f 1 5 0.2000 6.4000 8 JSON_HB 5B0A20202201222C0A20202202222C0A20202202222C0A20202203222C0A20202203222C0A20202204222C0A20202204222C0A20202205220A5D
test t1 a 0 49 0.0000 1.0000 8 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B2234222C202239222C20223135222C20223231222C20223239222C20223333222C20223339222C20223433225D0A7D
test t1 b vvvvvvvvvvvvv zzzzzzzzzzzzzzzzzz 0.2000 6.4000 8 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B0A202020202276767676767676767676767676222C0A202020202276767676767676767676767676222C0A202020202277777777777777777777777777777777777777777777777777777777222C0A202020202277777777777777777777777777777777777777777777777777777777222C0A20202020227878787878787878787878787878787878787878787878787878222C0A2020202022797979222C0A2020202022797979222C0A20202020227A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A7A220A20205D0A7D
test t1 c aaaa dddddddd 0.1250 7.0000 8 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B0A202020202261616161222C0A202020202261616161222C0A2020202022626262626262222C0A2020202022626262626262222C0A2020202022636363636363636363222C0A2020202022636363636363636363222C0A20202020226464646464646464222C0A20202020226464646464646464220A20205D0A7D
test t1 d 1989-03-12 1999-07-23 0.1500 8.5000 8 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B0A2020202022313938392D30332D3132222C0A2020202022313938392D30332D3132222C0A2020202022313939302D30352D3135222C0A2020202022313939302D30352D3135222C0A2020202022313939302D30352D3135222C0A2020202022313939302D30352D3135222C0A2020202022313939392D30372D3233222C0A2020202022313939392D30372D3233220A20205D0A7D
test t1 e 0.01 0.112 0.2250 6.2000 8 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B0A2020202022302E3031222C0A2020202022302E3031222C0A2020202022302E3031222C0A2020202022302E303132222C0A2020202022302E3035222C0A2020202022302E31222C0A2020202022302E31222C0A2020202022302E313132220A20205D0A7D
test t1 f 1 5 0.2000 6.4000 8 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B2201222C202202222C202202222C202203222C202203222C202204222C202204222C202205225D0A7D
DELETE FROM mysql.column_stats;
set histogram_size= 0;
set histogram_type=@SINGLE_PREC_TYPE;
......@@ -1502,109 +1502,111 @@ avg_length 4.0000
avg_frequency 2.7640
hist_size 100
hist_type JSON_HB
hex(histogram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
decode_histogram(hist_type,histogram) [
"0.0",
"0.0",
"0.0",
"0.0",
"0.0",
"0.0",
"0.1",
"0.1",
"0.2",
"0.2",
"0.3",
"0.3",
"0.4",
"0.4",
"0.4",
"0.5",
"0.5",
"0.6",
"0.6",
"0.7",
"0.7",
"0.8",
"0.9",
"1.1",
"1.2",
"1.3",
"1.4",
"1.4",
"1.6",
"1.6",
"1.7",
"1.9",
"2.0",
"2.2",
"2.2",
"2.3",
"2.5",
"2.6",
"2.8",
"2.9",
"3.1",
"3.2",
"3.4",
"3.6",
"3.8",
"4.0",
"4.3",
"4.5",
"4.8",
"5.1",
"5.4",
"5.7",
"5.8",
"6.1",
"6.4",
"6.8",
"7.2",
"7.5",
"7.7",
"8.1",
"8.5",
"8.8",
"9.1",
"9.5",
"10.1",
"10.8",
"11.3",
"12.0",
"12.6",
"13.5",
"14.2",
"16.1",
"16.8",
"18.1",
"20.0",
"21.6",
"23.4",
"28.3",
"31.7",
"34.1",
"37.5",
"41.9",
"46.4",
"50.7",
"55.1",
"60.4",
"65.6",
"72.6",
"77.1",
"81.2",
"85.6",
"87.7",
"89.9",
"92.1",
"94.2",
"95.9",
"97.3",
"98.1",
"99.0",
"99.9"
]
hex(histogram) 7B0A202022686973746F6772616D5F68625F7631223A205B0A2020202022302E30222C0A2020202022302E30222C0A2020202022302E30222C0A2020202022302E30222C0A2020202022302E30222C0A2020202022302E30222C0A2020202022302E31222C0A2020202022302E31222C0A2020202022302E32222C0A2020202022302E32222C0A2020202022302E33222C0A2020202022302E33222C0A2020202022302E34222C0A2020202022302E34222C0A2020202022302E34222C0A2020202022302E35222C0A2020202022302E35222C0A2020202022302E36222C0A2020202022302E36222C0A2020202022302E37222C0A2020202022302E37222C0A2020202022302E38222C0A2020202022302E39222C0A2020202022312E31222C0A2020202022312E32222C0A2020202022312E33222C0A2020202022312E34222C0A2020202022312E34222C0A2020202022312E36222C0A2020202022312E36222C0A2020202022312E37222C0A2020202022312E39222C0A2020202022322E30222C0A2020202022322E32222C0A2020202022322E32222C0A2020202022322E33222C0A2020202022322E35222C0A2020202022322E36222C0A2020202022322E38222C0A2020202022322E39222C0A2020202022332E31222C0A2020202022332E32222C0A2020202022332E34222C0A2020202022332E36222C0A2020202022332E38222C0A2020202022342E30222C0A2020202022342E33222C0A2020202022342E35222C0A2020202022342E38222C0A2020202022352E31222C0A2020202022352E34222C0A2020202022352E37222C0A2020202022352E38222C0A2020202022362E31222C0A2020202022362E34222C0A2020202022362E38222C0A2020202022372E32222C0A2020202022372E35222C0A2020202022372E37222C0A2020202022382E31222C0A2020202022382E35222C0A2020202022382E38222C0A2020202022392E31222C0A2020202022392E35222C0A202020202231302E31222C0A202020202231302E38222C0A202020202231312E33222C0A202020202231322E30222C0A202020202231322E36222C0A202020202231332E35222C0A202020202231342E32222C0A202020202231362E31222C0A202020202231362E38222C0A202020202231382E31222C0A202020202232302E30222C0A202020202232312E36222C0A202020202232332E34222C0A202020202232382E33222C0A202020202233312E37222C0A202020202233342E31222C0A202020202233372E35222C0A202020202234312E39222C0A202020202234362E34222C0A202020202235302E37222C0A202020202235352E31222C0A202020202236302E34222C0A202020202236352E36222C0A202020202237322E36222C0A202020202237372E31222C0A202020202238312E32222C0A202020202238352E36222C0A202020202238372E37222C0A202020202238392E39222C0A202020202239322E31222C0A202020202239342E32222C0A202020202239352E39222C0A202020202239372E33222C0A202020202239382E31222C0A202020202239392E30222C0A202020202239392E39220A20205D0A7D
decode_histogram(hist_type,histogram) {
"histogram_hb_v1": [
"0.0",
"0.0",
"0.0",
"0.0",
"0.0",
"0.0",
"0.1",
"0.1",
"0.2",
"0.2",
"0.3",
"0.3",
"0.4",
"0.4",
"0.4",
"0.5",
"0.5",
"0.6",
"0.6",
"0.7",
"0.7",
"0.8",
"0.9",
"1.1",
"1.2",
"1.3",
"1.4",
"1.4",
"1.6",
"1.6",
"1.7",
"1.9",
"2.0",
"2.2",
"2.2",
"2.3",
"2.5",
"2.6",
"2.8",
"2.9",
"3.1",
"3.2",
"3.4",
"3.6",
"3.8",
"4.0",
"4.3",
"4.5",
"4.8",
"5.1",
"5.4",
"5.7",
"5.8",
"6.1",
"6.4",
"6.8",
"7.2",
"7.5",
"7.7",
"8.1",
"8.5",
"8.8",
"9.1",
"9.5",
"10.1",
"10.8",
"11.3",
"12.0",
"12.6",
"13.5",
"14.2",
"16.1",
"16.8",
"18.1",
"20.0",
"21.6",
"23.4",
"28.3",
"31.7",
"34.1",
"37.5",
"41.9",
"46.4",
"50.7",
"55.1",
"60.4",
"65.6",
"72.6",
"77.1",
"81.2",
"85.6",
"87.7",
"89.9",
"92.1",
"94.2",
"95.9",
"97.3",
"98.1",
"99.0",
"99.9"
]
}
select UPPER(db_name),UPPER(table_name),UPPER(column_name),min_value,max_value,nulls_ratio,avg_length,avg_frequency,hist_size,hist_type,hex(histogram),decode_histogram(hist_type,histogram) from mysql.column_stats where UPPER(db_name)='WORLD' and UPPER(table_name)='CITY' and UPPER(column_name) = 'POPULATION';;
UPPER(db_name) WORLD
UPPER(table_name) CITY
......@@ -1616,263 +1618,265 @@ avg_length 4.0000
avg_frequency 1.0467
hist_size 254
hist_type JSON_HB
hex(histogram) 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"121000",
"121600",
"121954",
"122705",
"123359",
"123865",
"124207",
"124735",
"125255",
"125766",
"126282",
"126820",
"127222",
"127801",
"128300",
"129300",
"130000",
"131000",
"131717",
"132455",
"133106",
"133642",
"134037",
"135010",
"136216",
"137028",
"137776",
"138418",
"139283",
"140030",
"140800",
"142044",
"142659",
"143726",
"144582",
"145800",
"146439",
"147523",
"148105",
"149146",
"150100",
"151060",
"152442",
"153364",
"154980",
"155800",
"157300",
"158335",
"159632",
"161161",
"162300",
"163849",
"164747",
"166467",
"167461",
"169300",
"170428",
"171532",
"172701",
"173895",
"174985",
"176576",
"178182",
"179208",
"180210",
"181805",
"183100",
"184061",
"185401",
"186900",
"188344",
"189569",
"190905",
"193005",
"194300",
"195500",
"197254",
"199000",
"200901",
"202134",
"203793",
"206158",
"207588",
"210068",
"212976",
"214950",
"216735",
"218447",
"221000",
"222518",
"224887",
"227657",
"229425",
"233041",
"236000",
"239124",
"241649",
"243742",
"245772",
"248245",
"252386",
"254842",
"257812",
"262000",
"264081",
"266281",
"270251",
"272968",
"276421",
"279340",
"282941",
"286900",
"291000",
"294056",
"298900",
"301276",
"304477",
"309750",
"313530",
"317600",
"322267",
"326399",
"330276",
"334563",
"339131",
"342738",
"349246",
"353632",
"359147",
"362470",
"366549",
"372840",
"380755",
"385201",
"392830",
"400997",
"409100",
"416988",
"421589",
"428522",
"435964",
"443727",
"452976",
"461000",
"469735",
"476800",
"483155",
"493409",
"508899",
"519793",
"529900",
"540828",
"563662",
"580000",
"594501",
"616700",
"636765",
"656925",
"680332",
"703592",
"735167",
"764902",
"797735",
"830000",
"877239",
"940589",
"993400",
"1042740",
"1100000",
"1156100",
"1217818",
"1300977",
"1392860",
"1517550",
"1682000",
"1969868",
"2154376",
"2595674",
"2964638",
"4256300",
"6758845"
]
}
set histogram_type=@SINGLE_PREC_TYPE;
set histogram_size=0;
use test;
......@@ -1943,7 +1947,7 @@ nulls_ratio, avg_frequency,
hist_size, hist_type, HEX(histogram)
FROM mysql.column_stats;
db_name table_name column_name min_value max_value nulls_ratio avg_frequency hist_size hist_type HEX(histogram)
test t1 a 1 3 0.0000 1.0000 10 JSON_HB 5B0A20202231222C0A20202231222C0A20202231222C0A20202232222C0A20202232222C0A20202232222C0A20202232222C0A20202233222C0A20202233222C0A20202233220A5D
test t1 a 1 3 0.0000 1.0000 10 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B2231222C202231222C202231222C202232222C202232222C202232222C202232222C202233222C202233222C202233225D0A7D
set histogram_size=default;
drop table t1;
#
......@@ -1968,7 +1972,7 @@ nulls_ratio, avg_frequency,
hist_size, hist_type, HEX(histogram)
FROM mysql.column_stats;
db_name table_name column_name min_value max_value nulls_ratio avg_frequency hist_size hist_type HEX(histogram)
test t1 a 1 5 0.0000 1.0000 10 JSON_HB 5B0A20202231222C0A20202231222C0A20202232222C0A20202232222C0A20202233222C0A20202233222C0A20202234222C0A20202234222C0A20202235222C0A20202235220A5D
test t1 a 1 5 0.0000 1.0000 10 JSON_HB 7B0A202022686973746F6772616D5F68625F7631223A205B2231222C202231222C202232222C202232222C202233222C202233222C202234222C202234222C202235222C202235225D0A7D
set histogram_size=0;
set histogram_type=@SINGLE_PREC_TYPE;
drop table t1;
......@@ -2009,7 +2013,7 @@ nulls_ratio, avg_frequency,
hist_size, hist_type, HEX(histogram)
FROM mysql.column_stats;
db_name table_name column_name min_value max_value nulls_ratio avg_frequency hist_size hist_type HEX(histogram)
test t2 id 1 1024 0.0000 8.0000 63 JSON_HB 5B0A2020223137222C0A2020223333222C0A2020223439222C0A2020223635222C0A2020223831222C0A2020223937222C0A202022313133222C0A202022313239222C0A202022313435222C0A202022313631222C0A202022313737222C0A202022313933222C0A202022323039222C0A202022323235222C0A202022323431222C0A202022323537222C0A202022323733222C0A202022323839222C0A202022333035222C0A202022333231222C0A202022333337222C0A202022333533222C0A202022333639222C0A202022333835222C0A202022343031222C0A202022343137222C0A202022343333222C0A202022343439222C0A202022343635222C0A202022343831222C0A202022343937222C0A202022353133222C0A202022353239222C0A202022353435222C0A202022353631222C0A202022353737222C0A202022353933222C0A202022363039222C0A202022363235222C0A202022363431222C0A202022363537222C0A202022363733222C0A202022363839222C0A202022373035222C0A202022373231222C0A202022373337222C0A202022373533222C0A202022373639222C0A202022373835222C0A202022383031222C0A202022383137222C0A202022383333222C0A202022383439222C0A202022383635222C0A202022383831222C0A202022383937222C0A202022393133222C0A202022393239222C0A202022393435222C0A202022393631222C0A202022393737222C0A202022393933222C0A20202231303039220A5D
test t2 id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
set histogram_size=0;
drop table t1, t2;
set use_stat_tables=@save_use_stat_tables;
......@@ -2169,18 +2173,20 @@ select table_name, column_name, min_value, max_value, nulls_ratio, avg_length, a
DECODE_HISTOGRAM(hist_type, histogram)
from mysql.column_stats;
table_name column_name min_value max_value nulls_ratio avg_length avg_frequency DECODE_HISTOGRAM(hist_type, histogram)
t1 id 1 17384 0.0000 4.0000 14.0000 [
"1490",
"2979",
"4469",
"5958",
"7448",
"9937",
"11427",
"12916",
"14406",
"15895"
]
t1 id 1 17384 0.0000 4.0000 14.0000 {
"histogram_hb_v1": [
"1490",
"2979",
"4469",
"5958",
"7448",
"9937",
"11427",
"12916",
"14406",
"15895"
]
}
set analyze_sample_percentage=0.1;
#
# This query will show an innacurate avg_frequency value.
......@@ -2193,18 +2199,20 @@ select table_name, column_name, min_value, max_value, nulls_ratio, avg_length, a
DECODE_HISTOGRAM(hist_type, histogram)
from mysql.column_stats;
table_name column_name min_value max_value nulls_ratio avg_length avg_frequency DECODE_HISTOGRAM(hist_type, histogram)
t1 id 111 17026 0.0000 4.0000 10.4739 [
"832",
"2446",
"3422",
"5411",
"6687",
"9390",
"10738",
"12738",
"14365",
"15411"
]
t1 id 111 17026 0.0000 4.0000 10.4739 {
"histogram_hb_v1": [
"832",
"2446",
"3422",
"5411",
"6687",
"9390",
"10738",
"12738",
"14365",
"15411"
]
}
#
# This query will show a better avg_frequency value.
#
......@@ -2217,18 +2225,20 @@ select table_name, column_name, min_value, max_value, nulls_ratio, avg_length, a
DECODE_HISTOGRAM(hist_type, histogram)
from mysql.column_stats;
table_name column_name min_value max_value nulls_ratio avg_length avg_frequency DECODE_HISTOGRAM(hist_type, histogram)
t1 id 1 17384 0.0000 4.0000 14.0401 [
"1478",
"2954",
"4441",
"5894",
"7397",
"9888",
"11391",
"12895",
"14370",
"15880"
]
t1 id 1 17384 0.0000 4.0000 14.0401 {
"histogram_hb_v1": [
"1478",
"2954",
"4441",
"5894",
"7397",
"9888",
"11391",
"12895",
"14370",
"15880"
]
}
set analyze_sample_percentage=0;
#
# Test self adjusting sampling level.
......@@ -2241,18 +2251,20 @@ select table_name, column_name, min_value, max_value, nulls_ratio, avg_length, a
DECODE_HISTOGRAM(hist_type, histogram)
from mysql.column_stats;
table_name column_name min_value max_value nulls_ratio avg_length avg_frequency DECODE_HISTOGRAM(hist_type, histogram)
t1 id 1 17384 0.0000 4.0000 13.9812 [
"1500",
"3009",
"4501",
"5997",
"7493",
"9981",
"11456",
"12932",
"14408",
"15903"
]
t1 id 1 17384 0.0000 4.0000 13.9812 {
"histogram_hb_v1": [
"1500",
"3009",
"4501",
"5997",
"7493",
"9981",
"11456",
"12932",
"14408",
"15903"
]
}
#
# Test record estimation is working properly.
#
......@@ -2271,18 +2283,20 @@ select table_name, column_name, min_value, max_value, nulls_ratio, avg_length, a
DECODE_HISTOGRAM(hist_type, histogram)
from mysql.column_stats;
table_name column_name min_value max_value nulls_ratio avg_length avg_frequency DECODE_HISTOGRAM(hist_type, histogram)
t1 id 1 17384 0.0000 4.0000 14.0000 [
"1490",
"2979",
"4469",
"5958",
"7448",
"9937",
"11427",
"12916",
"14406",
"15895"
]
t1 id 1 17384 0.0000 4.0000 14.0000 {
"histogram_hb_v1": [
"1490",
"2979",
"4469",
"5958",
"7448",
"9937",
"11427",
"12916",
"14406",
"15895"
]
}
explain select * from t1;
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 229376
......@@ -2324,108 +2338,110 @@ test.t1_json analyze status Engine-independent statistics collected
test.t1_json analyze status OK
select * from mysql.column_stats where table_name='t1_json';
db_name table_name column_name min_value max_value nulls_ratio avg_length avg_frequency hist_size hist_type histogram
test t1_json a a-0 a-9 0.0000 3.0000 1.0000 100 JSON_HB [
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9"
]
test t1_json a a-0 a-9 0.0000 3.0000 1.0000 100 JSON_HB {
"histogram_hb_v1": [
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9"
]
}
explain extended select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE t1_json ALL NULL NULL NULL NULL 10 60.87 Using where
......@@ -2441,46 +2457,47 @@ Warnings:
Note 1003 select `test`.`t1_json`.`a` AS `a` from `test`.`t1_json` where `test`.`t1_json`.`a` < 'b-1a'
analyze select * from t1_json where a > 'zzzzzzzzz';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1_json ALL NULL NULL NULL NULL 10 10.00 0.00 0.00 Using where
1 SIMPLE t1_json ALL NULL NULL NULL NULL 10 10.00 10.00 0.00 Using where
drop table ten;
UPDATE mysql.column_stats SET histogram='["a-1", "a-2", {"a": "b"}, "a-3"]' WHERE table_name='t1_json';
FLUSH TABLES;
explain extended select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
ERROR HY000: Failed to parse histogram, encountered JSON_TYPE '1'.
create table users (
ERROR HY000: Failed to parse histogram: Root JSON element must be a JSON object at offset 1.
create table t2 (
city varchar(100)
);
set histogram_size=50;
insert into users select 'Moscow' from seq_1_to_99;
insert into users select 'Helsinki' from seq_1_to_2;
insert into t2 select 'Moscow' from seq_1_to_99;
insert into t2 select 'Helsinki' from seq_1_to_2;
set histogram_type=json_hb;
analyze table users persistent for all;
analyze table t2 persistent for all;
Table Op Msg_type Msg_text
test.users analyze status Engine-independent statistics collected
test.users analyze status OK
explain extended select * from users where city = 'Moscow';
test.t2 analyze status Engine-independent statistics collected
test.t2 analyze status OK
explain extended select * from t2 where city = 'Moscow';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 98.04 Using where
1 SIMPLE t2 ALL NULL NULL NULL NULL 101 98.04 Using where
Warnings:
Note 1003 select `test`.`users`.`city` AS `city` from `test`.`users` where `test`.`users`.`city` = 'Moscow'
analyze select * from users where city = 'Moscow';
Note 1003 select `test`.`t2`.`city` AS `city` from `test`.`t2` where `test`.`t2`.`city` = 'Moscow'
analyze select * from t2 where city = 'Moscow';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 101.00 98.04 98.02 Using where
explain extended select * from users where city = 'Helsinki';
1 SIMPLE t2 ALL NULL NULL NULL NULL 101 101.00 98.04 98.02 Using where
explain extended select * from t2 where city = 'Helsinki';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 2.00 Using where
1 SIMPLE t2 ALL NULL NULL NULL NULL 101 2.00 Using where
Warnings:
Note 1003 select `test`.`users`.`city` AS `city` from `test`.`users` where `test`.`users`.`city` = 'Helsinki'
analyze select * from users where city = 'helsinki';
Note 1003 select `test`.`t2`.`city` AS `city` from `test`.`t2` where `test`.`t2`.`city` = 'Helsinki'
analyze select * from t2 where city = 'helsinki';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 101.00 2.00 1.98 Using where
explain extended select * from users where city < 'Lagos';
1 SIMPLE t2 ALL NULL NULL NULL NULL 101 101.00 2.00 1.98 Using where
explain extended select * from t2 where city < 'Lagos';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 3.58 Using where
1 SIMPLE t2 ALL NULL NULL NULL NULL 101 50.00 Using where
Warnings:
Note 1003 select `test`.`users`.`city` AS `city` from `test`.`users` where `test`.`users`.`city` < 'Lagos'
Note 1003 select `test`.`t2`.`city` AS `city` from `test`.`t2` where `test`.`t2`.`city` < 'Lagos'
drop table t1_bin;
drop table t1_json;
drop table users;
drop table t2;
DELETE FROM mysql.column_stats;
create schema world;
use world;
......@@ -2489,630 +2506,654 @@ set histogram_size=50;
ANALYZE TABLE Country, City, CountryLanguage persistent for all;
SELECT column_name, min_value, max_value, hist_size, hist_type, histogram FROM mysql.column_stats;
column_name min_value max_value hist_size hist_type histogram
Code ABW ZWE 50 JSON_HB [
"ALB",
"ARM",
"AUS",
"BEL",
"BHR",
"BMU",
"BRN",
"CAN",
"CIV",
"COK",
"CUB",
"DEU",
"DOM",
"ESH",
"FJI",
"FSM",
"GIB",
"GNQ",
"GUF",
"HMD",
"IDN",
"IRQ",
"JAM",
"KGZ",
"KWT",
"LBY",
"LTU",
"MCO",
"MEX",
"MMR",
"MSR",
"MYS",
"NFK",
"NOR",
"PAK",
"PHL",
"PRK",
"QAT",
"RWA",
"SGS",
"SLV",
"STP",
"SWZ",
"TGO",
"TKM",
"TUR",
"UKR",
"UZB",
"VIR",
"YEM"
]
Name Afghanistan Zimbabwe 50 JSON_HB [
"Andorra",
"Argentina",
"Azerbaijan",
"Barbados",
"Bermuda",
"Bouvet Island",
"Bulgaria",
"Canada",
"Chile",
"Colombia",
"Costa Rica",
"Côte d’Ivoire",
"Dominican Republic",
"Equatorial Guinea",
"Faroe Islands",
"French Guiana",
"Georgia",
"Greenland",
"Guinea",
"Heard Island and McDonald Islands",
"Iceland",
"Ireland",
"Japan",
"Kuwait",
"Lesotho",
"Lithuania",
"Malawi",
"Marshall Islands",
"Mayotte",
"Mongolia",
"Namibia",
"Netherlands Antilles",
"Nigeria",
"Norway",
"Panama",
"Philippines",
"Qatar",
"Saint Helena",
"Saint Vincent and the Grenadines",
"Senegal",
"Slovenia",
"South Georgia and the South Sandwich Islands",
"Suriname",
"Syria",
"Thailand",
"Tunisia",
"Uganda",
"United States",
"Venezuela",
"Western Sahara"
]
SurfaceArea 0.40 17075400.00 50 JSON_HB [
"14.00",
"36.00",
"78.00",
"151.00",
"200.00",
"264.00",
"344.00",
"430.00",
"464.00",
"622.00",
"751.00",
"1399.00",
"2510.00",
"4033.00",
"8875.00",
"11000.00",
"14874.00",
"20256.00",
"25713.00",
"28051.00",
"30518.00",
"41526.00",
"48511.00",
"56785.00",
"69700.00",
"78866.00",
"90000.00",
"103000.00",
"111369.00",
"120538.00",
"147181.00",
"181035.00",
"214969.00",
"242900.00",
"274000.00",
"309500.00",
"331689.00",
"390757.00",
"447400.00",
"505992.00",
"581730.00",
"637657.00",
"774815.00",
"912050.00",
"1098581.00",
"1246700.00",
"1648195.00",
"2149690.00",
"2724900.00",
"9363520.00"
]
Population 0 1277558000 50 JSON_HB [
"0",
"1000",
"2500",
"8000",
"17000",
"27000",
"38000",
"68000",
"78000",
"99000",
"149000",
"190000",
"241000",
"307000",
"428000",
"456000",
"638000",
"885000",
"1295000",
"1726000",
"2153000",
"2662000",
"3101000",
"3520000",
"3850000",
"4023000",
"4629000",
"5074000",
"5398700",
"6188000",
"6782000",
"7733000",
"8329000",
"9586000",
"10239000",
"10730000",
"11385000",
"14786000",
"15942000",
"18886000",
"22244000",
"23115000",
"25662000",
"31471000",
"39441700",
"50456000",
"61399000",
"68470000",
"111506000",
"170115000"
]
Capital 1 4074 50 JSON_HB [
"35",
"63",
"129",
"150",
"187",
"204",
"538",
"554",
"586",
"652",
"764",
"904",
"917",
"926",
"937",
"1365",
"1464",
"1532",
"1800",
"1864",
"2256",
"2317",
"2409",
"2434",
"2441",
"2454",
"2463",
"2507",
"2514",
"2696",
"2728",
"2754",
"2821",
"2884",
"2914",
"2973",
"3018",
"3064",
"3161",
"3172",
"3208",
"3225",
"3248",
"3315",
"3334",
"3358",
"3425",
"3499",
"3537",
"3791"
]
ID 1 4079 50 JSON_HB [
"80",
"160",
"240",
"320",
"400",
"480",
"560",
"640",
"720",
"800",
"880",
"960",
"1040",
"1120",
"1200",
"1280",
"1360",
"1440",
"1520",
"1600",
"1680",
"1760",
"1840",
"1920",
"2000",
"2080",
"2160",
"2240",
"2320",
"2400",
"2480",
"2560",
"2640",
"2720",
"2800",
"2880",
"2960",
"3040",
"3120",
"3200",
"3280",
"3360",
"3440",
"3520",
"3600",
"3680",
"3760",
"3840",
"3920",
"4000"
]
Name A Coruña (La Coruña) Ürgenc 50 JSON_HB [
"Allentown",
"Araguari",
"Bahtim",
"Batangas",
"Bialystok",
"Brampton",
"Calama",
"Changchun",
"Ciomas",
"Cuautla",
"Detroit",
"Effon-Alaiye",
"Firozabad",
"Gebze",
"Guangyuan",
"Hangzhou",
"Hradec Králové",
"Inazawa",
"Jalib al-Shuyukh",
"Jubayl",
"Kassel",
"Kitakyushu",
"Kunshan",
"Le Mans",
"Longueuil",
"Malang",
"Mati",
"Mishan",
"Muroran",
"Natal",
"North York",
"Omsk",
"Palu",
"Phoenix",
"Poznan",
"Quezon",
"Rishra",
"Salem",
"Sancti-Spíritus",
"Sekondi-Takoradi",
"Silao",
"Stoke-on-Trent",
"Taegu",
"Teheran",
"Tomsk",
"Târgu Mures",
"Varginha",
"Weifang",
"Yangjiang",
"Zhaodong"
]
Country ABW ZWE 50 JSON_HB [
"ARM",
"BHS",
"BRA",
"BRA",
"BRA",
"CAN",
"CHN",
"CHN",
"CHN",
"CHN",
"CHN",
"COL",
"DEU",
"DZA",
"ESP",
"FRA",
"GBR",
"IDN",
"IDN",
"IND",
"IND",
"IND",
"IND",
"IRN",
"ITA",
"JPN",
"JPN",
"JPN",
"KOR",
"LKA",
"MEX",
"MEX",
"MMR",
"NGA",
"NZL",
"PER",
"PHL",
"POL",
"QAT",
"RUS",
"RUS",
"SAU",
"TCD",
"TUR",
"UKR",
"USA",
"USA",
"USA",
"USA",
"VNM"
]
Population 42 10500000 50 JSON_HB [
"50699",
"90601",
"92583",
"94600",
"96800",
"98781",
"100887",
"102681",
"105119",
"107329",
"109500",
"112375",
"115532",
"118718",
"121600",
"124207",
"126820",
"130000",
"133642",
"137776",
"142044",
"146439",
"151060",
"157300",
"163849",
"170428",
"176576",
"183100",
"189569",
"197254",
"206158",
"216735",
"227657",
"241649",
"254842",
"270251",
"286900",
"304477",
"326399",
"349246",
"372840",
"409100",
"443727",
"483155",
"540828",
"636765",
"764902",
"993400",
"1300977",
"2154376"
]
Country ABW ZWE 50 JSON_HB [
"ALB",
"ASM",
"AZE",
"BFA",
"BHS",
"BRA",
"CAF",
"CHE",
"CIV",
"COD",
"CPV",
"CZE",
"DOM",
"EST",
"FRA",
"GBR",
"GIN",
"GRC",
"HKG",
"IDN",
"IND",
"ISL",
"JPN",
"KGZ",
"LAO",
"LIE",
"LVA",
"MDA",
"MLI",
"MNG",
"MRT",
"MYS",
"NER",
"NIU",
"NRU",
"PAN",
"PLW",
"PYF",
"RUS",
"SDN",
"SLE",
"SVN",
"TCD",
"THA",
"TUR",
"TZA",
"UKR",
"UZB",
"VNM",
"ZAF"
]
Language Abhyasi [South]Mande 50 JSON_HB [
"Amhara",
"Arabic",
"Araucan",
"Bakhtyari",
"Belorussian",
"Bubi",
"Cebuano",
"Chinese",
"Comorian",
"Creole French",
"Danish",
"Embera",
"English",
"English",
"English",
"French",
"French",
"Futuna",
"German",
"Greek",
"Hakka",
"Hui",
"Italian",
"Joruba",
"Kazakh",
"Kongo",
"Kurdish",
"Luchazi",
"Makua",
"Malinke",
"Marshallese",
"Mixed Languages",
"Nauru",
"Nung",
"Pangasinan",
"Polish",
"Portuguese",
"Romanian",
"Russian",
"Sara",
"Shona",
"Songhai",
"Spanish",
"Spanish",
"Tamashek",
"Thai",
"Tswana",
"Tuvalu",
"Urdu",
"Wolea"
]
Percentage 0.0 99.9 50 JSON_HB [
"0.0",
"0.0",
"0.0",
"0.1",
"0.2",
"0.3",
"0.4",
"0.5",
"0.6",
"0.7",
"0.8",
"1.1",
"1.3",
"1.4",
"1.6",
"1.8",
"2.1",
"2.3",
"2.5",
"2.9",
"3.2",
"3.5",
"3.8",
"4.4",
"4.9",
"5.5",
"5.9",
"6.6",
"7.4",
"7.8",
"8.6",
"9.2",
"10.3",
"11.5",
"12.9",
"14.6",
"17.1",
"20.3",
"23.8",
"31.8",
"39.4",
"47.5",
"55.1",
"66.5",
"77.2",
"86.0",
"89.9",
"94.3",
"97.3",
"99.0"
]
Code ABW ZWE 50 JSON_HB {
"histogram_hb_v1": [
"ALB",
"ARM",
"AUS",
"BEL",
"BHR",
"BMU",
"BRN",
"CAN",
"CIV",
"COK",
"CUB",
"DEU",
"DOM",
"ESH",
"FJI",
"FSM",
"GIB",
"GNQ",
"GUF",
"HMD",
"IDN",
"IRQ",
"JAM",
"KGZ",
"KWT",
"LBY",
"LTU",
"MCO",
"MEX",
"MMR",
"MSR",
"MYS",
"NFK",
"NOR",
"PAK",
"PHL",
"PRK",
"QAT",
"RWA",
"SGS",
"SLV",
"STP",
"SWZ",
"TGO",
"TKM",
"TUR",
"UKR",
"UZB",
"VIR",
"YEM"
]
}
Name Afghanistan Zimbabwe 50 JSON_HB {
"histogram_hb_v1": [
"Andorra",
"Argentina",
"Azerbaijan",
"Barbados",
"Bermuda",
"Bouvet Island",
"Bulgaria",
"Canada",
"Chile",
"Colombia",
"Costa Rica",
"Côte d’Ivoire",
"Dominican Republic",
"Equatorial Guinea",
"Faroe Islands",
"French Guiana",
"Georgia",
"Greenland",
"Guinea",
"Heard Island and McDonald Islands",
"Iceland",
"Ireland",
"Japan",
"Kuwait",
"Lesotho",
"Lithuania",
"Malawi",
"Marshall Islands",
"Mayotte",
"Mongolia",
"Namibia",
"Netherlands Antilles",
"Nigeria",
"Norway",
"Panama",
"Philippines",
"Qatar",
"Saint Helena",
"Saint Vincent and the Grenadines",
"Senegal",
"Slovenia",
"South Georgia and the South Sandwich Islands",
"Suriname",
"Syria",
"Thailand",
"Tunisia",
"Uganda",
"United States",
"Venezuela",
"Western Sahara"
]
}
SurfaceArea 0.40 17075400.00 50 JSON_HB {
"histogram_hb_v1": [
"14.00",
"36.00",
"78.00",
"151.00",
"200.00",
"264.00",
"344.00",
"430.00",
"464.00",
"622.00",
"751.00",
"1399.00",
"2510.00",
"4033.00",
"8875.00",
"11000.00",
"14874.00",
"20256.00",
"25713.00",
"28051.00",
"30518.00",
"41526.00",
"48511.00",
"56785.00",
"69700.00",
"78866.00",
"90000.00",
"103000.00",
"111369.00",
"120538.00",
"147181.00",
"181035.00",
"214969.00",
"242900.00",
"274000.00",
"309500.00",
"331689.00",
"390757.00",
"447400.00",
"505992.00",
"581730.00",
"637657.00",
"774815.00",
"912050.00",
"1098581.00",
"1246700.00",
"1648195.00",
"2149690.00",
"2724900.00",
"9363520.00"
]
}
Population 0 1277558000 50 JSON_HB {
"histogram_hb_v1": [
"0",
"1000",
"2500",
"8000",
"17000",
"27000",
"38000",
"68000",
"78000",
"99000",
"149000",
"190000",
"241000",
"307000",
"428000",
"456000",
"638000",
"885000",
"1295000",
"1726000",
"2153000",
"2662000",
"3101000",
"3520000",
"3850000",
"4023000",
"4629000",
"5074000",
"5398700",
"6188000",
"6782000",
"7733000",
"8329000",
"9586000",
"10239000",
"10730000",
"11385000",
"14786000",
"15942000",
"18886000",
"22244000",
"23115000",
"25662000",
"31471000",
"39441700",
"50456000",
"61399000",
"68470000",
"111506000",
"170115000"
]
}
Capital 1 4074 50 JSON_HB {
"histogram_hb_v1": [
"35",
"63",
"129",
"150",
"187",
"204",
"538",
"554",
"586",
"652",
"764",
"904",
"917",
"926",
"937",
"1365",
"1464",
"1532",
"1800",
"1864",
"2256",
"2317",
"2409",
"2434",
"2441",
"2454",
"2463",
"2507",
"2514",
"2696",
"2728",
"2754",
"2821",
"2884",
"2914",
"2973",
"3018",
"3064",
"3161",
"3172",
"3208",
"3225",
"3248",
"3315",
"3334",
"3358",
"3425",
"3499",
"3537",
"3791"
]
}
ID 1 4079 50 JSON_HB {
"histogram_hb_v1": [
"80",
"160",
"240",
"320",
"400",
"480",
"560",
"640",
"720",
"800",
"880",
"960",
"1040",
"1120",
"1200",
"1280",
"1360",
"1440",
"1520",
"1600",
"1680",
"1760",
"1840",
"1920",
"2000",
"2080",
"2160",
"2240",
"2320",
"2400",
"2480",
"2560",
"2640",
"2720",
"2800",
"2880",
"2960",
"3040",
"3120",
"3200",
"3280",
"3360",
"3440",
"3520",
"3600",
"3680",
"3760",
"3840",
"3920",
"4000"
]
}
Name A Coruña (La Coruña) Ürgenc 50 JSON_HB {
"histogram_hb_v1": [
"Allentown",
"Araguari",
"Bahtim",
"Batangas",
"Bialystok",
"Brampton",
"Calama",
"Changchun",
"Ciomas",
"Cuautla",
"Detroit",
"Effon-Alaiye",
"Firozabad",
"Gebze",
"Guangyuan",
"Hangzhou",
"Hradec Králové",
"Inazawa",
"Jalib al-Shuyukh",
"Jubayl",
"Kassel",
"Kitakyushu",
"Kunshan",
"Le Mans",
"Longueuil",
"Malang",
"Mati",
"Mishan",
"Muroran",
"Natal",
"North York",
"Omsk",
"Palu",
"Phoenix",
"Poznan",
"Quezon",
"Rishra",
"Salem",
"Sancti-Spíritus",
"Sekondi-Takoradi",
"Silao",
"Stoke-on-Trent",
"Taegu",
"Teheran",
"Tomsk",
"Târgu Mures",
"Varginha",
"Weifang",
"Yangjiang",
"Zhaodong"
]
}
Country ABW ZWE 50 JSON_HB {
"histogram_hb_v1": [
"ARM",
"BHS",
"BRA",
"BRA",
"BRA",
"CAN",
"CHN",
"CHN",
"CHN",
"CHN",
"CHN",
"COL",
"DEU",
"DZA",
"ESP",
"FRA",
"GBR",
"IDN",
"IDN",
"IND",
"IND",
"IND",
"IND",
"IRN",
"ITA",
"JPN",
"JPN",
"JPN",
"KOR",
"LKA",
"MEX",
"MEX",
"MMR",
"NGA",
"NZL",
"PER",
"PHL",
"POL",
"QAT",
"RUS",
"RUS",
"SAU",
"TCD",
"TUR",
"UKR",
"USA",
"USA",
"USA",
"USA",
"VNM"
]
}
Population 42 10500000 50 JSON_HB {
"histogram_hb_v1": [
"50699",
"90601",
"92583",
"94600",
"96800",
"98781",
"100887",
"102681",
"105119",
"107329",
"109500",
"112375",
"115532",
"118718",
"121600",
"124207",
"126820",
"130000",
"133642",
"137776",
"142044",
"146439",
"151060",
"157300",
"163849",
"170428",
"176576",
"183100",
"189569",
"197254",
"206158",
"216735",
"227657",
"241649",
"254842",
"270251",
"286900",
"304477",
"326399",
"349246",
"372840",
"409100",
"443727",
"483155",
"540828",
"636765",
"764902",
"993400",
"1300977",
"2154376"
]
}
Country ABW ZWE 50 JSON_HB {
"histogram_hb_v1": [
"ALB",
"ASM",
"AZE",
"BFA",
"BHS",
"BRA",
"CAF",
"CHE",
"CIV",
"COD",
"CPV",
"CZE",
"DOM",
"EST",
"FRA",
"GBR",
"GIN",
"GRC",
"HKG",
"IDN",
"IND",
"ISL",
"JPN",
"KGZ",
"LAO",
"LIE",
"LVA",
"MDA",
"MLI",
"MNG",
"MRT",
"MYS",
"NER",
"NIU",
"NRU",
"PAN",
"PLW",
"PYF",
"RUS",
"SDN",
"SLE",
"SVN",
"TCD",
"THA",
"TUR",
"TZA",
"UKR",
"UZB",
"VNM",
"ZAF"
]
}
Language Abhyasi [South]Mande 50 JSON_HB {
"histogram_hb_v1": [
"Amhara",
"Arabic",
"Araucan",
"Bakhtyari",
"Belorussian",
"Bubi",
"Cebuano",
"Chinese",
"Comorian",
"Creole French",
"Danish",
"Embera",
"English",
"English",
"English",
"French",
"French",
"Futuna",
"German",
"Greek",
"Hakka",
"Hui",
"Italian",
"Joruba",
"Kazakh",
"Kongo",
"Kurdish",
"Luchazi",
"Makua",
"Malinke",
"Marshallese",
"Mixed Languages",
"Nauru",
"Nung",
"Pangasinan",
"Polish",
"Portuguese",
"Romanian",
"Russian",
"Sara",
"Shona",
"Songhai",
"Spanish",
"Spanish",
"Tamashek",
"Thai",
"Tswana",
"Tuvalu",
"Urdu",
"Wolea"
]
}
Percentage 0.0 99.9 50 JSON_HB {
"histogram_hb_v1": [
"0.0",
"0.0",
"0.0",
"0.1",
"0.2",
"0.3",
"0.4",
"0.5",
"0.6",
"0.7",
"0.8",
"1.1",
"1.3",
"1.4",
"1.6",
"1.8",
"2.1",
"2.3",
"2.5",
"2.9",
"3.2",
"3.5",
"3.8",
"4.4",
"4.9",
"5.5",
"5.9",
"6.6",
"7.4",
"7.8",
"8.6",
"9.2",
"10.3",
"11.5",
"12.9",
"14.6",
"17.1",
"20.3",
"23.8",
"31.8",
"39.4",
"47.5",
"55.1",
"66.5",
"77.2",
"86.0",
"89.9",
"94.3",
"97.3",
"99.0"
]
}
explain extended select * from Country where 'Code' between 'BBC' and 'GGG';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE Country ALL NULL NULL NULL NULL 239 100.00
......
mysql-test/main/statistics_json.test
View file @ 2a1cdbab
......@@ -37,6 +37,8 @@ analyze select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
explain extended select * from t1_json where a < 'b-1a';
analyze select * from t1_json where a > 'zzzzzzzzz';
drop table ten;
# test different valid JSON strings that are invalid histograms.
UPDATE mysql.column_stats SET histogram='["a-1", "a-2", {"a": "b"}, "a-3"]' WHERE table_name='t1_json';
FLUSH TABLES;
......@@ -45,23 +47,23 @@ explain extended select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
--source include/have_sequence.inc
create table users (
create table t2 (
city varchar(100)
);
set histogram_size=50;
insert into users select 'Moscow' from seq_1_to_99;
insert into users select 'Helsinki' from seq_1_to_2;
insert into t2 select 'Moscow' from seq_1_to_99;
insert into t2 select 'Helsinki' from seq_1_to_2;
set histogram_type=json_hb;
analyze table users persistent for all;
explain extended select * from users where city = 'Moscow';
analyze select * from users where city = 'Moscow';
explain extended select * from users where city = 'Helsinki';
analyze select * from users where city = 'helsinki';
explain extended select * from users where city < 'Lagos';
analyze table t2 persistent for all;
explain extended select * from t2 where city = 'Moscow';
analyze select * from t2 where city = 'Moscow';
explain extended select * from t2 where city = 'Helsinki';
analyze select * from t2 where city = 'helsinki';
explain extended select * from t2 where city < 'Lagos';
drop table t1_bin;
drop table t1_json;
drop table users;
drop table t2;
DELETE FROM mysql.column_stats;
......
sql/share/errmsg-utf8.txt
View file @ 2a1cdbab
......@@ -8914,4 +8914,4 @@ ER_PARTITION_CONVERT_SUBPARTITIONED
ER_PROVIDER_NOT_LOADED
eng "MariaDB tried to use the %s, but its provider plugin is not loaded"
ER_JSON_HISTOGRAM_PARSE_FAILED
eng "Failed to parse histogram, encountered JSON_TYPE '%d'."
eng "Failed to parse histogram: %s at offset %d."
sql/sql_statistics.cc
View file @ 2a1cdbab
......@@ -1123,6 +1123,7 @@ class Column_stat: public Stat_table
void get_stat_values()
{
table_field->read_stats->set_all_nulls();
// default: hist_type=NULL means there's no histogram
table_field->read_stats->histogram_type_on_disk= INVALID_HISTOGRAM;
if (table_field->read_stats->min_value)
......@@ -1196,7 +1197,10 @@ class Column_stat: public Stat_table
break;
}
case COLUMN_STAT_HISTOGRAM:
//TODO: if stat_field->length() == 0 then histogram_type_on_disk is set to INVALID_HISTOGRAM
/*
Do nothing here: we take the histogram length from the 'histogram'
column itself
*/
break;
}
}
......@@ -1245,7 +1249,7 @@ class Column_stat: public Stat_table
}
if (!hist->parse(mem_root, table_field,
table_field->read_stats->histogram_type_on_disk,
(const uchar*)val.ptr(), val.length()))
val.ptr(), val.length()))
{
table_field->read_stats->histogram_= hist;
return hist;
......@@ -1255,19 +1259,19 @@ class Column_stat: public Stat_table
}
};
bool Histogram_binary::parse(MEM_ROOT *mem_root, Field *,
Histogram_type type_arg,
const uchar *ptr_arg, uint size_arg)
bool Histogram_binary::parse(MEM_ROOT *mem_root, Field*,
Histogram_type type_arg, const char *hist_data,
size_t hist_data_len)
{
// Just copy the data
size = (uint8) size_arg;
type = type_arg;
if ((values = (uchar*)alloc_root(mem_root, size_arg)))
{
memcpy(values, ptr_arg, size_arg);
return false;
}
return true;
/* On-disk an in-memory formats are the same. Just copy the data. */
type= type_arg;
size= (uint8) hist_data_len; // 'size' holds the size of histogram in bytes
if (!(values= (uchar*)alloc_root(mem_root, hist_data_len)))
return true;
memcpy(values, hist_data, hist_data_len);
return false;
}
/*
......@@ -1307,39 +1311,81 @@ void Histogram_json::init_for_collection(MEM_ROOT *mem_root,
*/
bool Histogram_json::parse(MEM_ROOT *mem_root, Field *field,
Histogram_type type_arg, const uchar *ptr,
uint size_arg)
Histogram_type type_arg, const char *hist_data,
size_t hist_data_len)
{
DBUG_ENTER("Histogram_json::parse");
DBUG_ASSERT(type_arg == JSON_HB);
size = (uint8) size_arg;
const char *json = (char *)ptr;
int vt;
std::vector<std::string> hist_buckets_text;
bool result = json_get_array_items(json, json + strlen(json), &vt, hist_buckets_text);
if (!result)
{
my_error(ER_JSON_HISTOGRAM_PARSE_FAILED, MYF(0), vt);
DBUG_RETURN(true);
const char *err;
json_engine_t je;
json_string_t key_name;
json_scan_start(&je, &my_charset_utf8mb4_bin,
(const uchar*)hist_data,
(const uchar*)hist_data+hist_data_len);
if (json_read_value(&je) || je.value_type != JSON_VALUE_OBJECT)
{
err= "Root JSON element must be a JSON object";
goto error;
}
size= hist_buckets_text.size();
/*
Convert the text based array into a data structure that allows lookups and
estimates
*/
for (auto &s : hist_buckets_text)
json_string_set_str(&key_name, (const uchar*)JSON_NAME,
(const uchar*)JSON_NAME + strlen(JSON_NAME));
json_string_set_cs(&key_name, system_charset_info);
if (json_scan_next(&je) || je.state != JST_KEY ||
!json_key_matches(&je, &key_name))
{
field->store_text(s.data(), s.size(), &my_charset_bin);
err= "The first key in the object must be histogram_hb_v1";
goto error;
}
// Get the value in "truncated key tuple format" here:
uchar buf[MAX_KEY_LENGTH];
uint len_to_copy= field->key_length();
uint bytes= field->get_key_image(buf, len_to_copy, Field::itRAW);
histogram_bounds.push_back(std::string((char*)buf, bytes));
// The value must be a JSON array
if (json_read_value(&je) || (je.value_type != JSON_VALUE_ARRAY))
{
err= "A JSON array expected";
goto error;
}
// Read the array
while (!json_scan_next(&je))
{
switch(je.state)
{
case JST_VALUE:
{
const char *val;
int val_len;
json_smart_read_value(&je, &val, &val_len);
if (je.value_type != JSON_VALUE_STRING &&
je.value_type != JSON_VALUE_NUMBER &&
je.value_type != JSON_VALUE_TRUE &&
je.value_type != JSON_VALUE_FALSE)
{
err= "Scalar value expected";
goto error;
}
uchar buf[MAX_KEY_LENGTH];
uint len_to_copy= field->key_length();
field->store_text(val, val_len, &my_charset_bin);
uint bytes= field->get_key_image(buf, len_to_copy, Field::itRAW);
histogram_bounds.push_back(std::string((char*)buf, bytes));
// TODO: Should we also compare this endpoint with the previous
// to verify that the ordering is right?
break;
}
case JST_ARRAY_END:
break;
}
}
size= histogram_bounds.size();
DBUG_RETURN(false);
error:
my_error(ER_JSON_HISTOGRAM_PARSE_FAILED, MYF(0), err,
je.s.c_str - (const uchar*)hist_data);
DBUG_RETURN(true);
}
......@@ -1347,7 +1393,7 @@ static
void store_key_image_to_rec_no_null(Field *field, uchar *ptr) {
MY_BITMAP *old_map= dbug_tmp_use_all_columns(field->table,
&field->table->write_set);
field->set_key_image(ptr, field->key_length());
field->set_key_image(ptr, field->key_length());
dbug_tmp_restore_column_map(&field->table->write_set, old_map);
}
......@@ -1506,9 +1552,9 @@ double Histogram_json::point_selectivity(Field *field, key_range *endpoint, doub
/*
@param field The table field histogram is for. We don't care about the
field's current value, we only need its virtual functions to
field's current value, we only need its virtual functions to
perform various operations
@param min_endp, max_endp - this specifies the range.
*/
double Histogram_json::range_selectivity(Field *field, key_range *min_endp,
......@@ -1594,7 +1640,7 @@ double Histogram_json::range_selectivity(Field *field, key_range *min_endp,
void Histogram_json::serialize(Field *field)
{
field->store((char*)json_text, strlen((char*)json_text), &my_charset_bin);
field->store(json_text.data(), json_text.size(), &my_charset_bin);
}
......@@ -2052,13 +2098,16 @@ class Histogram_builder_json : public Histogram_builder
}
void build_json_from_histogram() {
Json_writer *writer = new Json_writer();
writer->start_array();
Json_writer writer;
writer.start_object();
writer.add_member(Histogram_json::JSON_NAME).start_array();
for(auto& value: bucket_bounds) {
writer->add_str(value.c_str());
writer.add_str(value.c_str());
}
writer->end_array();
Binary_string *json_string = (Binary_string *) writer->output.get_string();
writer.end_array();
writer.end_object();
Binary_string *json_string = (Binary_string *) writer.output.get_string();
Histogram_json *hist= (Histogram_json*)histogram;
hist->set_json_text(bucket_bounds.size(), (uchar *) json_string->c_ptr());
}
......@@ -2080,42 +2129,6 @@ Histogram_base *create_histogram(Histogram_type hist_type)
}
bool json_get_array_items(const char *json, const char *json_end, int *value_type, std::vector<std::string> &container) {
json_engine_t je;
int vl;
const char *v;
json_scan_start(&je, &my_charset_utf8mb4_bin, (const uchar *)json, (const uchar *)json_end);
if (json_read_value(&je) || (*value_type = je.value_type) != JSON_VALUE_ARRAY)
{
return false;
}
std::string val;
while(!json_scan_next(&je))
{
switch(je.state)
{
case JST_VALUE:
*value_type = json_smart_read_value(&je, &v, &vl);
if (je.value_type != JSON_VALUE_STRING &&
je.value_type != JSON_VALUE_NUMBER &&
je.value_type != JSON_VALUE_TRUE &&
je.value_type != JSON_VALUE_FALSE)
{
return false;
}
val = std::string(v, vl);
container.emplace_back(val);
break;
case JST_ARRAY_END:
break;
}
}
return true;
}
C_MODE_START
int histogram_build_walk(void *elem, element_count elem_cnt, void *arg)
......
sql/sql_statistics.h
View file @ 2a1cdbab
......@@ -152,7 +152,7 @@ class Histogram_base : public Sql_alloc
{
public:
virtual bool parse(MEM_ROOT *mem_root, Field *field, Histogram_type type_arg,
const uchar *ptr, uint size)= 0;
const char *hist_data, size_t hist_data_len)= 0;
virtual void serialize(Field *to_field)= 0;
virtual Histogram_type get_type()=0;
......@@ -187,7 +187,7 @@ class Histogram_binary : public Histogram_base
{
public:
bool parse(MEM_ROOT *mem_root, Field *, Histogram_type type_arg,
const uchar *ptr_arg, uint size_arg) override;
const char *hist_data, size_t hist_data_len) override;
void serialize(Field *to_field) override;
Histogram_type get_type() override { return type; }
......@@ -350,14 +350,16 @@ class Histogram_json : public Histogram_base
uint8 size; /* Number of elements in the histogram */
/* Collection-time only: collected histogram in the JSON form. */
uchar *json_text;
std::string json_text;
// Array of histogram bucket endpoints in KeyTupleFormat.
std::vector<std::string> histogram_bounds;
public:
static constexpr const char* JSON_NAME="histogram_hb_v1";
bool parse(MEM_ROOT *mem_root, Field *field, Histogram_type type_arg,
const uchar *ptr, uint size) override;
const char *hist_data, size_t hist_data_len) override;
void serialize(Field *field) override;
......@@ -375,7 +377,8 @@ class Histogram_json : public Histogram_base
void set_json_text(ulonglong sz, uchar *json_text_arg)
{
size = (uint8) sz;
json_text= json_text_arg;
json_text.assign((const char*)json_text_arg,
strlen((const char*)json_text_arg));
}
uint get_size() override
......@@ -481,8 +484,9 @@ class Column_statistics
ulonglong avg_frequency;
public:
/* Histogram type as specified in mysql.column_stats.hist_type */
Histogram_type histogram_type_on_disk;
Histogram_base *histogram_;
uint32 no_values_provided_bitmap()
......
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