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Merge pull request #45961 from ClickHouse/vdimir/sparkbar-fix
This commit is contained in:
Vladimir C
GitHub
commit
e3712bb2c6
@ -1,5 +1,5 @@
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---
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slug: /en/sql-reference/aggregate-functions/reference/sparkbar
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slug: /en/sql-reference/aggregate-functions/reference/sparkbar
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sidebar_position: 311
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sidebar_label: sparkbar
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---
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@ -7,9 +7,11 @@ sidebar_label: sparkbar
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# sparkbar
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The function plots a frequency histogram for values `x` and the repetition rate `y` of these values over the interval `[min_x, max_x]`.
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Repetitions for all `x` falling into the same bucket are averaged, so data should be pre-aggregated.
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Negative repetitions are ignored.
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If no interval is specified, then the minimum `x` is used as the interval start, and the maximum `x` — as the interval end.
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If no interval is specified, then the minimum `x` is used as the interval start, and the maximum `x` — as the interval end.
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Otherwise, values outside the interval are ignored.
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**Syntax**
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@ -37,29 +39,24 @@ sparkbar(width[, min_x, max_x])(x, y)
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Query:
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``` sql
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CREATE TABLE spark_bar_data (`cnt` UInt64,`event_date` Date) ENGINE = MergeTree ORDER BY event_date SETTINGS index_granularity = 8192;
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INSERT INTO spark_bar_data VALUES(1,'2020-01-01'),(4,'2020-01-02'),(5,'2020-01-03'),(2,'2020-01-04'),(3,'2020-01-05'),(7,'2020-01-06'),(6,'2020-01-07'),(8,'2020-01-08'),(2,'2020-01-11');
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CREATE TABLE spark_bar_data (`value` Int64, `event_date` Date) ENGINE = MergeTree ORDER BY event_date;
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SELECT sparkbar(9)(event_date,cnt) FROM spark_bar_data;
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INSERT INTO spark_bar_data VALUES (1,'2020-01-01'), (3,'2020-01-02'), (4,'2020-01-02'), (-3,'2020-01-02'), (5,'2020-01-03'), (2,'2020-01-04'), (3,'2020-01-05'), (7,'2020-01-06'), (6,'2020-01-07'), (8,'2020-01-08'), (2,'2020-01-11');
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SELECT sparkbar(9,toDate('2020-01-01'),toDate('2020-01-10'))(event_date,cnt) FROM spark_bar_data;
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SELECT sparkbar(9)(event_date,cnt) FROM (SELECT sum(value) as cnt, event_date FROM spark_bar_data GROUP BY event_date);
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SELECT sparkbar(9, toDate('2020-01-01'), toDate('2020-01-10'))(event_date,cnt) FROM (SELECT sum(value) as cnt, event_date FROM spark_bar_data GROUP BY event_date);
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```
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Result:
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``` text
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┌─sparkbar(9)(event_date, cnt)─┐
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│ │
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│ ▁▅▄▃██▅ ▁ │
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│ │
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│ ▂▅▂▃▆█ ▂ │
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└──────────────────────────────┘
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┌─sparkbar(9, toDate('2020-01-01'), toDate('2020-01-10'))(event_date, cnt)─┐
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│ │
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│▁▄▄▂▅▇█▁ │
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│ │
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│ ▂▅▂▃▇▆█ │
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└──────────────────────────────────────────────────────────────────────────┘
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```
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@ -1,14 +1,15 @@
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---
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slug: /ru/sql-reference/aggregate-functions/reference/sparkbar
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slug: /ru/sql-reference/aggregate-functions/reference/sparkbar
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sidebar_position: 311
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sidebar_label: sparkbar
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---
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# sparkbar {#sparkbar}
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Функция строит гистограмму частот по заданным значениям `x` и частоте повторения этих значений `y` на интервале `[min_x, max_x]`.
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Функция строит гистограмму частот по заданным значениям `x` и частоте повторения этих значений `y` на интервале `[min_x, max_x]`. Повторения для всех `x`, попавших в один бакет, усредняются, поэтому данные должны быть предварительно агрегированы. Отрицательные повторения игнорируются.
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Если интервал для построения не указан, то в качестве нижней границы интервала будет взято минимальное значение `x`, а в качестве верхней границы — максимальное значение `x`.
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Значения `x` вне указанного интервала игнорируются.
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**Синтаксис**
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@ -39,29 +40,23 @@ sparkbar(width[, min_x, max_x])(x, y)
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Запрос:
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``` sql
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CREATE TABLE spark_bar_data (`cnt` UInt64,`event_date` Date) ENGINE = MergeTree ORDER BY event_date SETTINGS index_granularity = 8192;
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INSERT INTO spark_bar_data VALUES(1,'2020-01-01'),(4,'2020-01-02'),(5,'2020-01-03'),(2,'2020-01-04'),(3,'2020-01-05'),(7,'2020-01-06'),(6,'2020-01-07'),(8,'2020-01-08'),(2,'2020-01-11');
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CREATE TABLE spark_bar_data (`value` Int64, `event_date` Date) ENGINE = MergeTree ORDER BY event_date;
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SELECT sparkbar(9)(event_date,cnt) FROM spark_bar_data;
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INSERT INTO spark_bar_data VALUES (1,'2020-01-01'), (3,'2020-01-02'), (4,'2020-01-02'), (-3,'2020-01-02'), (5,'2020-01-03'), (2,'2020-01-04'), (3,'2020-01-05'), (7,'2020-01-06'), (6,'2020-01-07'), (8,'2020-01-08'), (2,'2020-01-11');
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SELECT sparkbar(9,toDate('2020-01-01'),toDate('2020-01-10'))(event_date,cnt) FROM spark_bar_data;
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SELECT sparkbar(9)(event_date,cnt) FROM (SELECT sum(value) as cnt, event_date FROM spark_bar_data GROUP BY event_date);
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SELECT sparkbar(9, toDate('2020-01-01'), toDate('2020-01-10'))(event_date,cnt) FROM (SELECT sum(value) as cnt, event_date FROM spark_bar_data GROUP BY event_date);
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```
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Результат:
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``` text
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┌─sparkbar(9)(event_date, cnt)─┐
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│ │
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│ ▁▅▄▃██▅ ▁ │
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│ │
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│ ▂▅▂▃▆█ ▂ │
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└──────────────────────────────┘
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┌─sparkbar(9, toDate('2020-01-01'), toDate('2020-01-10'))(event_date, cnt)─┐
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│ │
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│▁▄▄▂▅▇█▁ │
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│ │
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│ ▂▅▂▃▇▆█ │
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└──────────────────────────────────────────────────────────────────────────┘
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```
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@ -50,11 +50,13 @@ AggregateFunctionPtr createAggregateFunctionSparkbar(const std::string & name, c
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assertBinary(name, arguments);
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if (params.size() != 1 && params.size() != 3)
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throw Exception(ErrorCodes::NUMBER_OF_ARGUMENTS_DOESNT_MATCH, "The number of params does not match for aggregate function {}", name);
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throw Exception(ErrorCodes::NUMBER_OF_ARGUMENTS_DOESNT_MATCH,
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"The number of params does not match for aggregate function '{}', expected 1 or 3, got {}", name, params.size());
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if (params.size() == 3)
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{
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if (params.at(1).getType() != arguments[0]->getDefault().getType() || params.at(2).getType() != arguments[0]->getDefault().getType())
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if (params.at(1).getType() != arguments[0]->getDefault().getType() ||
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params.at(2).getType() != arguments[0]->getDefault().getType())
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{
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throw Exception(ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT,
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"The second and third parameters are not the same type as the first arguments for aggregate function {}", name);
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@ -63,7 +65,6 @@ AggregateFunctionPtr createAggregateFunctionSparkbar(const std::string & name, c
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return createAggregateFunctionSparkbarImpl(name, *arguments[0], *arguments[1], arguments, params);
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}
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}
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void registerAggregateFunctionSparkbar(AggregateFunctionFactory & factory)
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@ -18,10 +18,15 @@
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namespace DB
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{
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namespace ErrorCodes
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{
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extern const int BAD_ARGUMENTS;
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}
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template<typename X, typename Y>
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struct AggregateFunctionSparkbarData
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{
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/// TODO: calculate histogram instead of storing all points
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using Points = HashMap<X, Y>;
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Points points;
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@ -31,20 +36,26 @@ struct AggregateFunctionSparkbarData
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Y min_y = std::numeric_limits<Y>::max();
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Y max_y = std::numeric_limits<Y>::lowest();
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void insert(const X & x, const Y & y)
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Y insert(const X & x, const Y & y)
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{
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auto result = points.insert({x, y});
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if (!result.second)
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result.first->getMapped() += y;
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if (isNaN(y) || y <= 0)
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return 0;
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auto [it, inserted] = points.insert({x, y});
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if (!inserted)
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it->getMapped() += y;
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return it->getMapped();
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}
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void add(X x, Y y)
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{
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insert(x, y);
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auto new_y = insert(x, y);
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min_x = std::min(x, min_x);
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max_x = std::max(x, max_x);
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min_y = std::min(y, min_y);
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max_y = std::max(y, max_y);
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max_y = std::max(new_y, max_y);
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}
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void merge(const AggregateFunctionSparkbarData & other)
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@ -53,10 +64,14 @@ struct AggregateFunctionSparkbarData
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return;
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for (auto & point : other.points)
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insert(point.getKey(), point.getMapped());
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{
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auto new_y = insert(point.getKey(), point.getMapped());
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max_y = std::max(new_y, max_y);
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}
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min_x = std::min(other.min_x, min_x);
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max_x = std::max(other.max_x, max_x);
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min_y = std::min(other.min_y, min_y);
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max_y = std::max(other.max_y, max_y);
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}
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@ -85,7 +100,6 @@ struct AggregateFunctionSparkbarData
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size_t size;
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readVarUInt(size, buf);
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/// TODO Protection against huge size
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X x;
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Y y;
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for (size_t i = 0; i < size; ++i)
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@ -95,7 +109,6 @@ struct AggregateFunctionSparkbarData
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insert(x, y);
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}
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}
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};
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template<typename X, typename Y>
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@ -104,16 +117,17 @@ class AggregateFunctionSparkbar final
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{
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private:
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size_t width;
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X min_x;
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X max_x;
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bool specified_min_max_x;
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const size_t width = 0;
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template <class T>
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size_t updateFrame(ColumnString::Chars & frame, const T value) const
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/// Range for x specified in parameters.
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const bool is_specified_range_x = false;
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const X begin_x = std::numeric_limits<X>::min();
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const X end_x = std::numeric_limits<X>::max();
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size_t updateFrame(ColumnString::Chars & frame, Y value) const
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{
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static constexpr std::array<std::string_view, 9> bars{" ", "▁", "▂", "▃", "▄", "▅", "▆", "▇", "█"};
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const auto & bar = (isNaN(value) || value > 8 || value < 1) ? bars[0] : bars[static_cast<UInt8>(value)];
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const auto & bar = (isNaN(value) || value < 1 || 8 < value) ? bars[0] : bars[static_cast<UInt8>(value)];
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frame.insert(bar.begin(), bar.end());
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return bar.size();
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}
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@ -122,161 +136,108 @@ private:
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* The minimum value of y is rendered as the lowest height "▁",
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* the maximum value of y is rendered as the highest height "█", and the middle value will be rendered proportionally.
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* If a bucket has no y value, it will be rendered as " ".
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* If the actual number of buckets is greater than the specified bucket, it will be compressed by width.
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* For example, there are actually 11 buckets, specify 10 buckets, and divide the 11 buckets as follows (11/10):
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* 0.0-1.1, 1.1-2.2, 2.2-3.3, 3.3-4.4, 4.4-5.5, 5.5-6.6, 6.6-7.7, 7.7-8.8, 8.8-9.9, 9.9-11.
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* The y value of the first bucket will be calculated as follows:
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* the actual y value of the first position + the actual second position y*0.1, and the remaining y*0.9 is reserved for the next bucket.
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* The next bucket will use the last y*0.9 + the actual third position y*0.2, and the remaining y*0.8 will be reserved for the next bucket. And so on.
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*/
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void render(ColumnString & to_column, const AggregateFunctionSparkbarData<X, Y> & data) const
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{
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size_t sz = 0;
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auto & values = to_column.getChars();
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auto & offsets = to_column.getOffsets();
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auto update_column = [&] ()
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if (data.points.empty())
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{
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values.push_back('\0');
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offsets.push_back(offsets.empty() ? 1 : offsets.back() + 1);
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return;
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}
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auto from_x = is_specified_range_x ? begin_x : data.min_x;
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auto to_x = is_specified_range_x ? end_x : data.max_x;
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if (from_x >= to_x)
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{
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size_t sz = updateFrame(values, 8);
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values.push_back('\0');
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offsets.push_back(offsets.empty() ? sz + 1 : offsets.back() + sz + 1);
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};
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if (data.points.empty() || !width)
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return update_column();
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size_t diff_x;
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X min_x_local;
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if (specified_min_max_x)
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{
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diff_x = max_x - min_x;
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min_x_local = min_x;
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}
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else
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{
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diff_x = data.max_x - data.min_x;
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min_x_local = data.min_x;
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return;
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}
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if ((diff_x + 1) <= width)
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{
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Y min_y = data.min_y;
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Y max_y = data.max_y;
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Float64 diff_y = max_y - min_y;
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PaddedPODArray<Y> histogram(width, 0);
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PaddedPODArray<UInt64> fhistogram(width, 0);
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if (diff_y != 0.0)
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for (const auto & point : data.points)
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{
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if (point.getKey() < from_x || to_x < point.getKey())
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continue;
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X delta = to_x - from_x;
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if (delta < std::numeric_limits<X>::max())
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delta = delta + 1;
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X value = point.getKey() - from_x;
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Float64 w = histogram.size();
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size_t index = std::min<size_t>(static_cast<size_t>(w / delta * value), histogram.size() - 1);
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if (std::numeric_limits<Y>::max() - histogram[index] > point.getMapped())
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{
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for (size_t i = 0; i <= diff_x; ++i)
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{
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auto it = data.points.find(static_cast<X>(min_x_local + i));
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bool found = it != data.points.end();
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sz += updateFrame(values, found ? std::round(((it->getMapped() - min_y) / diff_y) * 7) + 1 : 0.0);
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}
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histogram[index] += point.getMapped();
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fhistogram[index] += 1;
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}
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else
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{
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for (size_t i = 0; i <= diff_x; ++i)
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sz += updateFrame(values, data.points.has(min_x_local + static_cast<X>(i)) ? 1 : 0);
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/// In case of overflow, just saturate
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histogram[index] = std::numeric_limits<Y>::max();
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}
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}
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else
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for (size_t i = 0; i < histogram.size(); ++i)
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{
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// begin reshapes to width buckets
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Float64 multiple_d = (diff_x + 1) / static_cast<Float64>(width);
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std::optional<Float64> min_y;
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std::optional<Float64> max_y;
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std::optional<Float64> new_y;
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std::vector<std::optional<Float64>> new_points;
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new_points.reserve(width);
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std::pair<size_t, Float64> bound{0, 0.0};
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size_t cur_bucket_num = 0;
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// upper bound for bucket
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auto upper_bound = [&](size_t bucket_num)
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{
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bound.second = (bucket_num + 1) * multiple_d;
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bound.first = static_cast<size_t>(std::floor(bound.second));
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};
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upper_bound(cur_bucket_num);
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for (size_t i = 0; i <= (diff_x + 1); ++i)
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{
|
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if (i == bound.first) // is bound
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{
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Float64 proportion = bound.second - bound.first;
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auto it = data.points.find(min_x_local + static_cast<X>(i));
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bool found = (it != data.points.end());
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if (found && proportion > 0)
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new_y = new_y.value_or(0) + it->getMapped() * proportion;
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if (new_y)
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{
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Float64 avg_y = new_y.value() / multiple_d;
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new_points.emplace_back(avg_y);
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// If min_y has no value, or if the avg_y of the current bucket is less than min_y, update it.
|
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if (!min_y || avg_y < min_y)
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min_y = avg_y;
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if (!max_y || avg_y > max_y)
|
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max_y = avg_y;
|
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}
|
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else
|
||||
{
|
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new_points.emplace_back();
|
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}
|
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|
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// next bucket
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||||
new_y = found ? ((1 - proportion) * it->getMapped()) : std::optional<Float64>();
|
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upper_bound(++cur_bucket_num);
|
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}
|
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else
|
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{
|
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auto it = data.points.find(min_x_local + static_cast<X>(i));
|
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if (it != data.points.end())
|
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new_y = new_y.value_or(0) + it->getMapped();
|
||||
}
|
||||
}
|
||||
|
||||
if (!min_y || !max_y) // No value is set
|
||||
return update_column();
|
||||
|
||||
Float64 diff_y = max_y.value() - min_y.value();
|
||||
|
||||
auto update_frame = [&] (const std::optional<Float64> & point_y)
|
||||
{
|
||||
sz += updateFrame(values, point_y ? std::round(((point_y.value() - min_y.value()) / diff_y) * 7) + 1 : 0);
|
||||
};
|
||||
auto update_frame_for_constant = [&] (const std::optional<Float64> & point_y)
|
||||
{
|
||||
sz += updateFrame(values, point_y ? 1 : 0);
|
||||
};
|
||||
|
||||
if (diff_y != 0.0)
|
||||
std::for_each(new_points.begin(), new_points.end(), update_frame);
|
||||
else
|
||||
std::for_each(new_points.begin(), new_points.end(), update_frame_for_constant);
|
||||
if (fhistogram[i] > 0)
|
||||
histogram[i] /= fhistogram[i];
|
||||
}
|
||||
update_column();
|
||||
|
||||
Y y_max = 0;
|
||||
for (auto & y : histogram)
|
||||
{
|
||||
if (isNaN(y) || y <= 0)
|
||||
continue;
|
||||
y_max = std::max(y_max, y);
|
||||
}
|
||||
|
||||
if (y_max == 0)
|
||||
{
|
||||
values.push_back('\0');
|
||||
offsets.push_back(offsets.empty() ? 1 : offsets.back() + 1);
|
||||
return;
|
||||
}
|
||||
|
||||
for (auto & y : histogram)
|
||||
{
|
||||
if (isNaN(y) || y <= 0)
|
||||
y = 0;
|
||||
else
|
||||
y = y * 7 / y_max + 1;
|
||||
}
|
||||
|
||||
size_t sz = 0;
|
||||
for (const auto & y : histogram)
|
||||
sz += updateFrame(values, y);
|
||||
|
||||
values.push_back('\0');
|
||||
offsets.push_back(offsets.empty() ? sz + 1 : offsets.back() + sz + 1);
|
||||
}
|
||||
|
||||
|
||||
public:
|
||||
AggregateFunctionSparkbar(const DataTypes & arguments, const Array & params)
|
||||
: IAggregateFunctionDataHelper<AggregateFunctionSparkbarData<X, Y>, AggregateFunctionSparkbar>(
|
||||
arguments, params, std::make_shared<DataTypeString>())
|
||||
: IAggregateFunctionDataHelper<AggregateFunctionSparkbarData<X, Y>, AggregateFunctionSparkbar>(arguments, params, std::make_shared<DataTypeString>())
|
||||
, width(params.empty() ? 0 : params.at(0).safeGet<UInt64>())
|
||||
, is_specified_range_x(params.size() >= 3)
|
||||
, begin_x(is_specified_range_x ? static_cast<X>(params.at(1).safeGet<X>()) : std::numeric_limits<X>::min())
|
||||
, end_x(is_specified_range_x ? static_cast<X>(params.at(2).safeGet<X>()) : std::numeric_limits<X>::max())
|
||||
{
|
||||
width = params.at(0).safeGet<UInt64>();
|
||||
if (params.size() == 3)
|
||||
{
|
||||
specified_min_max_x = true;
|
||||
min_x = static_cast<X>(params.at(1).safeGet<X>());
|
||||
max_x = static_cast<X>(params.at(2).safeGet<X>());
|
||||
}
|
||||
else
|
||||
{
|
||||
specified_min_max_x = false;
|
||||
min_x = std::numeric_limits<X>::min();
|
||||
max_x = std::numeric_limits<X>::max();
|
||||
}
|
||||
if (width < 2 || 1024 < width)
|
||||
throw Exception(ErrorCodes::BAD_ARGUMENTS, "Parameter width must be in range [2, 1024]");
|
||||
|
||||
if (begin_x >= end_x)
|
||||
throw Exception(ErrorCodes::BAD_ARGUMENTS, "Parameter `min_x` must be less than `max_x`");
|
||||
}
|
||||
|
||||
String getName() const override
|
||||
@ -287,7 +248,7 @@ public:
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * /*arena*/) const override
|
||||
{
|
||||
X x = assert_cast<const ColumnVector<X> *>(columns[0])->getData()[row_num];
|
||||
if (min_x <= x && x <= max_x)
|
||||
if (begin_x <= x && x <= end_x)
|
||||
{
|
||||
Y y = assert_cast<const ColumnVector<Y> *>(columns[1])->getData()[row_num];
|
||||
this->data(place).add(x, y);
|
||||
|
||||
@ -1,26 +1,69 @@
|
||||
▁
|
||||
▁█
|
||||
▃█▁
|
||||
▄▅█▁
|
||||
▄▄█▇▁
|
||||
▃▄▅█▃▁
|
||||
▂▅▃▇█▁▂
|
||||
▂▅▃▅██ ▁
|
||||
▁▅▄▃██▅ ▁
|
||||
▁▄▄▂▅▇█▂ ▂
|
||||
-- { echoOn }
|
||||
|
||||
SELECT sparkbar(2)(event_date,cnt) FROM spark_bar_test;
|
||||
▅█
|
||||
SELECT sparkbar(3)(event_date,cnt) FROM spark_bar_test;
|
||||
▄█▃
|
||||
SELECT sparkbar(4)(event_date,cnt) FROM spark_bar_test;
|
||||
▄▅█▃
|
||||
SELECT sparkbar(5)(event_date,cnt) FROM spark_bar_test;
|
||||
▃▂▆█▂
|
||||
SELECT sparkbar(6)(event_date,cnt) FROM spark_bar_test;
|
||||
▃▄▆█ ▃
|
||||
SELECT sparkbar(7)(event_date,cnt) FROM spark_bar_test;
|
||||
▂▃▃▆█ ▂
|
||||
SELECT sparkbar(8)(event_date,cnt) FROM spark_bar_test;
|
||||
▂▅▂▇▆█ ▂
|
||||
SELECT sparkbar(9)(event_date,cnt) FROM spark_bar_test;
|
||||
▂▅▂▃▆█ ▂
|
||||
SELECT sparkbar(10)(event_date,cnt) FROM spark_bar_test;
|
||||
▂▅▂▃▇▆█ ▂
|
||||
SELECT sparkbar(11)(event_date,cnt) FROM spark_bar_test;
|
||||
▁▄▅▂▃▇▆█ ▂
|
||||
SELECT sparkbar(11,2,5)(event_date,cnt) FROM spark_bar_test;
|
||||
|
||||
SELECT sparkbar(11,3,7)(event_date,cnt) FROM spark_bar_test;
|
||||
|
||||
SELECT sparkbar(11,4,11)(event_date,cnt) FROM spark_bar_test;
|
||||
|
||||
SELECT sparkbar(11,toDate('2020-01-02'),toDate('2020-01-05'))(event_date,cnt) FROM spark_bar_test;
|
||||
▆ █ ▃ ▅
|
||||
SELECT sparkbar(11,toDate('2020-01-03'),toDate('2020-01-07'))(event_date,cnt) FROM spark_bar_test;
|
||||
▆ ▃ ▄ █ ▇
|
||||
SELECT sparkbar(11,toDate('2020-01-04'),toDate('2020-01-11'))(event_date,cnt) FROM spark_bar_test;
|
||||
▂▃▇ ▆█ ▂
|
||||
SELECT sparkbar(2,toDate('2020-01-01'),toDate('2020-01-08'))(event_date,cnt) FROM spark_bar_test;
|
||||
▄█
|
||||
SELECT sparkbar(2,toDate('2020-01-02'),toDate('2020-01-09'))(event_date,cnt) FROM spark_bar_test;
|
||||
▄█
|
||||
SELECT sparkbar(3,toDate('2020-01-01'),toDate('2020-01-09'))(event_date,cnt) FROM spark_bar_test;
|
||||
▄▅█
|
||||
SELECT sparkbar(3,toDate('2020-01-01'),toDate('2020-01-10'))(event_date,cnt) FROM spark_bar_test;
|
||||
▃▅█
|
||||
SELECT sparkbar(4,toDate('2020-01-01'),toDate('2020-01-08'))(event_date,cnt) FROM spark_bar_test;
|
||||
▃▄▆█
|
||||
SELECT sparkbar(5,toDate('2020-01-01'),toDate('2020-01-10'))(event_date,cnt) FROM spark_bar_test;
|
||||
▃▄▆█
|
||||
SELECT sparkbar(9,toDate('2020-01-01'),toDate('2020-01-10'))(event_date,cnt) FROM spark_bar_test;
|
||||
▂▅▂▃▇▆█
|
||||
WITH number DIV 50 AS k, number % 50 AS value SELECT k, sparkbar(50, 0, 99)(number, value) FROM numbers(100) GROUP BY k ORDER BY k;
|
||||
0 ▁▁▁▁▂▂▂▃▃▃▃▄▄▄▅▅▅▅▆▆▆▇▇▇█
|
||||
1 ▁▁▁▁▂▂▂▃▃▃▃▄▄▄▅▅▅▅▆▆▆▇▇▇█
|
||||
SELECT sparkbar(128, 0, 9223372036854775806)(toUInt64(9223372036854775806), number % 65535) FROM numbers(100);
|
||||
█
|
||||
SELECT sparkbar(128)(toUInt64(9223372036854775806), number % 65535) FROM numbers(100);
|
||||
█
|
||||
SELECT sparkbar(9)(x, y) FROM (SELECT * FROM Values('x UInt64, y UInt8', (18446744073709551615,255), (0,0), (0,0), (4036797895307271799,254)));
|
||||
▇ █
|
||||
SELECT sparkbar(8, 0, 7)((number + 1) % 8, 1), sparkbar(8, 0, 7)((number + 2) % 8, 1), sparkbar(8, 0, 7)((number + 3) % 8, 1) FROM numbers(7);
|
||||
███████ █ ██████ ██ █████
|
||||
SELECT sparkbar(2)(number, -number) FROM numbers(10);
|
||||
|
||||
SELECT sparkbar(10)(number, number - 7) FROM numbers(10);
|
||||
▄█
|
||||
SELECT sparkbar(1024)(number, number) FROM numbers(1024);
|
||||
▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█
|
||||
SELECT sparkbar(1024)(number, 1) FROM numbers(1024);
|
||||
████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████
|
||||
SELECT sparkbar(1024)(number, 0) FROM numbers(1024);
|
||||
|
||||
▁
|
||||
▆█▁▃
|
||||
▅▁▂█▇
|
||||
▁▂▇▆█ ▁
|
||||
▁█
|
||||
▁█
|
||||
▁▄█
|
||||
▂█▁
|
||||
▁▃▅█
|
||||
▁▃▅█
|
||||
0 ▁▁▂▂▂▂▃▃▃▄▄▄▅▅▅▅▆▆▆▇▇▇▇██
|
||||
1 ▁▁▂▂▂▂▃▃▃▄▄▄▅▅▅▅▆▆▆▇▇▇▇██
|
||||
|
||||
@ -4,7 +4,8 @@ CREATE TABLE spark_bar_test (`cnt` UInt64,`event_date` Date) ENGINE = MergeTree
|
||||
|
||||
INSERT INTO spark_bar_test VALUES(1,'2020-01-01'),(4,'2020-01-02'),(5,'2020-01-03'),(2,'2020-01-04'),(3,'2020-01-05'),(7,'2020-01-06'),(6,'2020-01-07'),(8,'2020-01-08'),(2,'2020-01-11');
|
||||
|
||||
SELECT sparkbar(1)(event_date,cnt) FROM spark_bar_test;
|
||||
-- { echoOn }
|
||||
|
||||
SELECT sparkbar(2)(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(3)(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(4)(event_date,cnt) FROM spark_bar_test;
|
||||
@ -20,7 +21,6 @@ SELECT sparkbar(11,2,5)(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(11,3,7)(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(11,4,11)(event_date,cnt) FROM spark_bar_test;
|
||||
|
||||
SELECT sparkbar(11,toDate('2020-01-02'),toDate('2020-01-02'))(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(11,toDate('2020-01-02'),toDate('2020-01-05'))(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(11,toDate('2020-01-03'),toDate('2020-01-07'))(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(11,toDate('2020-01-04'),toDate('2020-01-11'))(event_date,cnt) FROM spark_bar_test;
|
||||
@ -31,14 +31,32 @@ SELECT sparkbar(3,toDate('2020-01-01'),toDate('2020-01-09'))(event_date,cnt) FRO
|
||||
SELECT sparkbar(3,toDate('2020-01-01'),toDate('2020-01-10'))(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(4,toDate('2020-01-01'),toDate('2020-01-08'))(event_date,cnt) FROM spark_bar_test;
|
||||
SELECT sparkbar(5,toDate('2020-01-01'),toDate('2020-01-10'))(event_date,cnt) FROM spark_bar_test;
|
||||
|
||||
DROP TABLE IF EXISTS spark_bar_test;
|
||||
SELECT sparkbar(9,toDate('2020-01-01'),toDate('2020-01-10'))(event_date,cnt) FROM spark_bar_test;
|
||||
|
||||
WITH number DIV 50 AS k, number % 50 AS value SELECT k, sparkbar(50, 0, 99)(number, value) FROM numbers(100) GROUP BY k ORDER BY k;
|
||||
|
||||
-- OOM guard
|
||||
DROP TABLE IF EXISTS spark_bar_oom;
|
||||
CREATE TABLE spark_bar_oom (x UInt64, y UInt8) Engine=MergeTree ORDER BY tuple();
|
||||
INSERT INTO spark_bar_oom VALUES (18446744073709551615,255),(0,0),(0,0),(4036797895307271799,163);
|
||||
SELECT sparkbar(9)(x,y) FROM spark_bar_oom SETTINGS max_memory_usage = 100000000; -- { serverError 241 }
|
||||
DROP TABLE IF EXISTS spark_bar_oom;
|
||||
SELECT sparkbar(128, 0, 9223372036854775806)(toUInt64(9223372036854775806), number % 65535) FROM numbers(100);
|
||||
SELECT sparkbar(128)(toUInt64(9223372036854775806), number % 65535) FROM numbers(100);
|
||||
SELECT sparkbar(9)(x, y) FROM (SELECT * FROM Values('x UInt64, y UInt8', (18446744073709551615,255), (0,0), (0,0), (4036797895307271799,254)));
|
||||
|
||||
SELECT sparkbar(8, 0, 7)((number + 1) % 8, 1), sparkbar(8, 0, 7)((number + 2) % 8, 1), sparkbar(8, 0, 7)((number + 3) % 8, 1) FROM numbers(7);
|
||||
|
||||
SELECT sparkbar(2)(number, -number) FROM numbers(10);
|
||||
SELECT sparkbar(10)(number, number - 7) FROM numbers(10);
|
||||
SELECT sparkbar(1024)(number, number) FROM numbers(1024);
|
||||
SELECT sparkbar(1024)(number, 1) FROM numbers(1024);
|
||||
SELECT sparkbar(1024)(number, 0) FROM numbers(1024);
|
||||
|
||||
-- { echoOff }
|
||||
|
||||
SELECT sparkbar(0)(number, number) FROM numbers(10); -- { serverError BAD_ARGUMENTS }
|
||||
SELECT sparkbar(1)(number, number) FROM numbers(10); -- { serverError BAD_ARGUMENTS }
|
||||
SELECT sparkbar(1025)(number, number) FROM numbers(10); -- { serverError BAD_ARGUMENTS }
|
||||
SELECT sparkbar(2, 10, 9)(number, number) FROM numbers(10); -- { serverError BAD_ARGUMENTS }
|
||||
SELECT sparkbar(2, -5, -1)(number, number) FROM numbers(10); -- { serverError ILLEGAL_TYPE_OF_ARGUMENT }
|
||||
SELECT sparkbar(2, -5, 1)(number, number) FROM numbers(10); -- { serverError ILLEGAL_TYPE_OF_ARGUMENT }
|
||||
SELECT sparkbar(2)(toInt32(number), number) FROM numbers(10); -- { serverError ILLEGAL_TYPE_OF_ARGUMENT }
|
||||
SELECT sparkbar(2, 0)(number, number) FROM numbers(10); -- { serverError NUMBER_OF_ARGUMENTS_DOESNT_MATCH }
|
||||
SELECT sparkbar(2, 0, 5, 8)(number, number) FROM numbers(10); -- { serverError NUMBER_OF_ARGUMENTS_DOESNT_MATCH }
|
||||
|
||||
DROP TABLE IF EXISTS spark_bar_test;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user