task up to arrays
This commit is contained in:
dr0zd
@@ -0,0 +1,23 @@
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--task 1
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select
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user_id,
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indexOf(tags, 'promo') as promo_index,
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arrayJoin(tags)
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from events
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where has(tags, 'promo')
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-- task 2
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select
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user_id,
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scores['math'] as math_score,
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mapValues(scores) as all_values
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from metrics
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-- task 3
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select
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name,
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contact.type as contact_type,
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contact.value as contact_value
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from users_nested
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array join contacts as contact
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where contact.type = 'email'
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@@ -0,0 +1,61 @@
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-- task 1
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CREATE TABLE raw_data (
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user_id String,
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balance String,
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created_at String
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) ENGINE = MergeTree ORDER BY tuple();
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select
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user_id,
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toDecimal64OrNull(balance, 2) as balance,
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toTimeDate64OrNull(created_at, 3) as created_at
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from raw_data
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where
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toDecimal64OrNull(balance, 2) is not null and
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toTimeDate64OrNull(created_at, 3) is not null
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-- task 2 (failed)
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CREATE TABLE events (
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event_id String,
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event_date String, -- форматы: "2023-01-01", "01.02.2023", "invalid"
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event_time String -- форматы: "12:30:45", "25:99:99"
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);
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select
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event_id,
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toStartOfHour(toDateTimeOrNull(concatWithSeparator(' ', events_date, events_time)))
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from events
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where
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toDateOrNull(event_date) is not null and toTimeOrNull(event_time) is not null
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-- task 3
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CREATE TABLE user_activity (
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user_id UInt32,
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actions String -- JSON: ["login", "purchase", "logout"]
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);
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SELECT
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user_id,
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actions_arr,
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length(actions_arr) AS actions_count
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FROM
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(
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SELECT
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user_id,
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JSONExtract(actions, 'Array(String)') AS actions_arr
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FROM user_activity
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)
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WHERE has(actions_arr, 'purchase');
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-- task 4
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CREATE TABLE sensor_data (
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sensor_id UInt32,
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value Float64,
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status Enum('ok' = 1, 'error' = 2)
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);
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SELECT
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toString(status) as status,
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avg(value) as avg_value
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from sensor_data
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where
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toDecimal64OrNull(value, 2) is not null
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group by status
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@@ -0,0 +1,103 @@
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--task 1
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create table mdrozdov.products (
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product_id Int,
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name String
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)
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engine = MergeTree
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order by product_id
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insert into mdrozdov.products values
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(101, 'iPhone 14'),
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(102, 'Galaxy S22'),
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(103, 'Pixel 7')
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create table mdrozdov.prices (
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product_id Int,
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price Int,
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region String
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)
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engine = MergeTree
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order by product_id
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insert into mdrozdov.prices values
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(101, 999, 'US'),
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(101, 1049, 'EU'),
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(102, 850, 'US'),
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(102, 899, 'CA'),
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(103, 799, 'JP')
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-- 1)
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select
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product_id,
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name,
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price,
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region
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from mdrozdov.products
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any left join mdrozdov.prices
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on mdrozdov.products.product_id = mdrozdov.prices.product_id
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-- 2)
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create table mdrozdov.ticks
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ON CLUSTER clickhouse_cluster (
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time DateTime,
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symbol String,
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price Decimal(10, 2)
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)
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engine = ReplicatedMergeTree(
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'/clickhouse/tables/{shard}/mdrozdov/ticks',
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'{replica}'
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)
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order by (time, symbol)
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insert into mdrozdov.ticks values
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('2025-07-17 10:00:00', 'AAPL', 190.5),
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('2025-07-17 10:01:00', 'AAPL', 191.2),
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('2025-07-17 10:02:30', 'AAPL', 192.0),
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('2025-07-17 10:05:00', 'GOOG', 2850.0)
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create table mdrozdov.orders
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ON CLUSTER clickhouse_cluster (
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time DateTime,
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symbol String,
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size Int
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)
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engine = ReplicatedMergeTree(
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'/clickhouse/tables/{shard}/mdrozdov/orders',
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'{replica}'
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)
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order by size
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insert into mdrozdov.orders values
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('2025-07-17 10:00:30', 'AAPL', 50),
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('2025-07-17 10:02:00', 'AAPL', 75),
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('2025-07-17 10:03:00', 'AAPL', 20),
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('2025-07-17 10:04:00', 'GOOG', 15)
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select
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o.time,
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o.symbol,
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t.price as last_price
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from mdrozdov.orders o
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asof join mdrozdov.ticks t
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on o.symbol = t.symbol and o.time >= t.time
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-- task 3
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select
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user_id,
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name
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from users
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where user_id in (
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select user_id
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from payments
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where amount > 1000
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)
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-- task 4
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select
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bl.user_id,
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u.name,
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bl.event_time,
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bl.event_type,
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from big_logs bl
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any left join users u
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using(user_id)
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@@ -0,0 +1,64 @@
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--page_views table
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create table page_views (
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user_id UInt64,
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url String,
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view_time DateTime
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)
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Engine = MergeTree
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Order by (user_id, view_time)
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Partition by toYYYYMM(view_time)
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-- users table
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create table users(
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id UInt64,
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name String,
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updated_at DateTime
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)
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ENGINE = ReplacingMergeTree(updated_at)
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Order by id;
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-- region_sales table
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create table region_sales(
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region String,
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date Date,
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sales UInt64
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)
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ENGINE = SummingMergeTree
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Partition by toYYYYMM(date)
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Order by (region, date)
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insert into mdrozdov.region_sales (region, date, sales)
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values ('Russia', '2025-01-14', 30), ('Russia', '2025-01-16', 22), ('USA', '2025-01-14', 1400)
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OPTIMIZE TABLE mdrozdov.region_sales FINAL
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-- user_metrics table
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create table mdrozdov.user_metrics (
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region String,
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avg_age_state AggregateFunction(avg, UInt8),
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active_users_state AggregateFunction(uniq, UInt64)
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)
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Engine = AggregatingMergeTree
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Order by region
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INSERT INTO mdrozdov.user_metrics
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SELECT
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'Moscow' AS region,
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avgState(toUInt8(25)) AS avg_age_state,
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uniqState(toUInt64(100)) AS active_users_state
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UNION ALL
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SELECT
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'Moscow',
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avgState(toUInt8(30)),
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uniqState(toUInt64(50))
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UNION ALL
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SELECT
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'SPB',
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avgState(toUInt8(20)),
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uniqState(toUInt64(10));
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SELECT
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region,
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avgMerge(avg_age_state) AS avg_age,
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uniqMerge(active_users_state) AS active_users
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FROM mdrozdov.user_metrics
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GROUP BY region
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@@ -0,0 +1,136 @@
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CREATE TABLE users (
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user_id Int,
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name String,
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age Int,
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country String,
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is_active bool
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)
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engine = MergeTree
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order by user_id
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insert into mdrozdov.users values
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(1, 'Ivan' ,30, 'RU', 1),
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(2, 'Anna' ,25, 'RU', 1),
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(3, 'Petr' ,45, 'RU', 0),
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(4, 'Olga' ,35, 'RU', 1),
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(5, 'John' ,55, 'US', 1),
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(6, 'Alice' ,42, 'US', 0),
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(7, 'Tom' ,38, 'US', 1),
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(8, 'Lucas' ,28, 'BR', 1),
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(9, 'Maria' ,60, 'BR', 1),
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(10, 'João' ,27, 'BR', 0),
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(11, 'Kenji' ,33, 'JP', 1),
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(12, 'Yuki' ,29, 'JP', 0),
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(13, 'Chen' ,40, 'CN', 1),
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(14, 'Li' ,48, 'CN', 1),
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(15, 'Fatima',31, 'AE', 1),
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(16, 'Ahmed' ,36, 'AE', 1),
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(17, 'George',24, 'US', 1),
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(18, 'Nina' ,34, 'RU', 1),
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(19, 'Max' ,50, 'DE', 1),
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(20, 'Sophie',22, 'DE', 0)
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--1. Получи 10 самых старших **активных** пользователей.
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select
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user_id,
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name,
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age,
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country,
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is_active
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from mdrozdov.users
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where is_active
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order by age desc
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limit 10
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--2. Выведи пользователей из `country = 'RU'`, отсортированных по имени.
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select
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user_id,
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name,
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age,
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country,
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is_active
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from mdrozdov.users
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where country = 'RU'
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order by name asc
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--3. Что произойдёт, если написать `LIMIT 10` **без `ORDER BY`**?
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-- ответ будет недетерминирован
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--4. Посчитай количество пользователей по странам.
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select
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country,
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count(user_id) as total_users
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from mdrozdov.users
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group by country
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--5. Для каждой страны выведи минимальный и максимальный возраст.
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select
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country,
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min(age) as min_user_age,
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max(age) as max_user_age
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from mdrozdov.users
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group by country
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--6. Отсортируй страны по убыванию количества пользователей.
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select
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country,
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count(user_id) as total_users
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from mdrozdov.users
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group by country
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order by total_users desc
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-- task 2
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CREATE TABLE mdrozdov.events (
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user_id Int,
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event_time DateTime,
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event_type String --mb better enum but idc
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)
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engine = MergeTree
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order by user_id
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insert into events values
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(1, '2025-07-17 09:00:00', 'click'),
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(1, '2025-07-17 09:05:00', 'view'),
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(1, '2025-07-17 09:10:00', 'purchase'),
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(2, '2025-07-17 10:00:00', 'click'),
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(2, '2025-07-17 10:05:00', 'click'),
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(2, '2025-07-17 11:00:00', 'view'),
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(3, '2025-07-16 12:00:00', 'view'),
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(3, '2025-07-16 12:30:00', 'click'),
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(3, '2025-07-17 08:00:00', 'purchase'),
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(4, '2025-07-17 13:00:00', 'click'),
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(4, '2025-07-17 14:00:00', 'view'),
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(4, '2025-07-17 15:00:00', 'view'),
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(5, '2025-07-16 20:00:00', 'view'),
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(5, '2025-07-17 01:00:00', 'click'),
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(5, '2025-07-17 06:00:00', 'purchase'),
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(6, '2025-07-17 07:30:00', 'view'),
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(6, '2025-07-17 08:45:00', 'click'),
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(7, '2025-07-16 23:59:59', 'click'),
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(7, '2025-07-17 00:01:00', 'purchase'),
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(7, '2025-07-17 10:10:00', 'view')
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--1-2) Добавь колонку с кумулятивным количеством событий по user_id (используй count() OVER ...)
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select
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user_id,
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event_time,
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event_type,
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count(*) over (partition by user_id order by event_time) as total_click_exact_moment,
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row_number() over (partition by user_id order by event_time) as row_number
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from mdrozdov.events
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--3) да, поддерживается, но не обязательно для коммулятивного суммирования строк
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--4-6) Сделай WITH recent_events AS (...) — все события за последние 24 часа.
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with recent_events AS (
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select *
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from mdrozdov.events
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where event_time >= '2025-07-18'::DATE - interval '1 day'
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), category_list as (
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select 'click' as event_type, 'interaction' as category
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union all
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select 'view', 'interaction'
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union all
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select 'purchase', 'conversion'
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)
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select
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user_id,
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count(*) as total_events_last_24h,
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count(distinct cl.category) as uniq_categories
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from recent_events re
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left join category_list cl
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using(event_type)
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group by user_id
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order by total_events_last_24h desc, user_id asc
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limit 5
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@@ -0,0 +1,33 @@
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-- task 1
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CREATE TABLE dist_table
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ENGINE = Distributed(
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'cluster_name', -- нет доступа к конфигу infra clickhouse
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'mdrozdov',
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'logs',
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rand()
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);
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--rand() это параметр по которому мы распределяем данные при insert на разные ноды, в данном
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--случае нам это нужно для равномерности распределения, потому что таблица не требует особых связей или тп
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-- task 2
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--Создай VIEW top_active_users, который показывает топ-100 пользователей по числу событий
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CREATE VIEW top_active_users AS
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select user_id, count(*) as total_events
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from events
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group by user_id
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order by total_events desc
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limit 100
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-- не подходит для дашборда с миллионами строк, потому что вычисляется каждый раз при вызове
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-- для дашбордов лучше подойдет materialized view, тк хранит данные запроса и обновляется автоматически
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-- при вставке новых данных
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--task 3
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CREATE MATERIALIZED VIEW
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ENGINE = SummingMergeTree
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order by date
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mv_clicks_per_day AS
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select
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toDate(event_time) as date,
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count(*) as total_clicks
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from raw_events
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group date
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Block a user