ClickHouse Documentation
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Table of Contents
What Is ClickHouse?
Key Properties of OLAP Scenario
Why Column-Oriented Databases Work Better in the OLAP Scenario
Input/output
CPU
Distinctive Features of ClickHouse
True Column-Oriented Database Management System
Data Compression
Disk Storage of Data
Parallel Processing on Multiple Cores
Distributed Processing on Multiple Servers
SQL Support
Vector Computation Engine
Real-time Data Updates
Primary Index
Secondary Indexes
Suitable for Online Queries
Support for Approximated Calculations
Adaptive Join Algorithm
Data Replication and Data Integrity Support
Role-Based Access Control
Features that Can Be Considered Disadvantages
Performance
Throughput for a Single Large Query
Latency When Processing Short Queries
Throughput When Processing a Large Quantity of Short Queries
Performance When Inserting Data
ClickHouse History
Usage in Yandex.Metrica and Other Yandex Services
Aggregated and Non-aggregated Data
ClickHouse Adopters
Getting Started
Example Datasets
GitHub Events Dataset
Anonymized Yandex.Metrica Data
Obtaining Tables from Prepared Partitions
Obtaining Tables from Compressed TSV File
Example Queries
Recipes Dataset
Download and Unpack the Dataset
Create a Table
Insert the Data
Validate the Inserted Data
Example Queries
Top Components by the Number of Recipes:
The Most Complex Recipes with Strawberry
Online Playground
Star Schema Benchmark
WikiStat
Terabyte of Click Logs from Criteo
AMPLab Big Data Benchmark
Brown University Benchmark
New York Taxi Data
How to Import the Raw Data
Download of Prepared Partitions
Results on Single Server
Summary
Crowdsourced air traffic data from The OpenSky Network 2020
Download the Dataset
Create the Table
Import Data
Validate the Data
Run Some Queries
Most busy origin airports and the average distance seen
Number of flights from three major Moscow airports, weekly
Online Playground
UK Property Price Paid
Download the Dataset
Create the Table
Preprocess and Import Data
Validate the Data
Run Some Queries
Query 1. Average Price Per Year
Query 2. Average Price per Year in London
Query 3. The Most Expensive Neighborhoods
Let's Speed Up Queries Using Projections
Build a Projection
Test Performance
Query 1. Average Price Per Year
Query 2. Average Price Per Year in London
Query 3. The Most Expensive Neighborhoods
Summary
Test It in Playground
Cell Towers
Get the Dataset
Examples
Use case
New York Public Library "What's on the Menu?" Dataset
Download the Dataset
Unpack the Dataset
Create the Tables
Import Data
Denormalize the Data
Validate the Data
Run Some Queries
Burger Prices:
Vodka:
Caviar:
Test it in Playground
OnTime
Import from Raw Data
Download of Prepared Partitions
Queries
Installation
System Requirements
Available Installation Options
From DEB Packages
Packages
From RPM Packages
From Tgz Archives
From Docker Image
Single Binary
From Precompiled Binaries for Non-Standard Environments
From Sources
Launch
ClickHouse Tutorial
What to Expect from This Tutorial?
Single Node Setup
Import Sample Dataset
Download and Extract Table Data
Create Tables
Import Data
Example Queries
Cluster Deployment
ClickHouse Playground
Credentials
Limitations
Examples
Implementation Details
Interfaces
Command-line Client
Usage
Queries with Parameters
Query Syntax
Example
Configuring
Command Line Options
Configuration Files
Query ID Format
Native Interface (TCP)
HTTP Interface
Compression
Default Database
Response Buffering
Queries with Parameters
Example
Predefined HTTP Interface
predefined_query_handler
dynamic_query_handler
static
MySQL Interface
Formats for Input and Output Data
TabSeparated
Data Formatting
TabSeparatedRaw
TabSeparatedWithNames
TabSeparatedWithNamesAndTypes
Template
TemplateIgnoreSpaces
TSKV
CSV
CSVWithNames
CustomSeparated
JSON
JSONStrings
JSONAsString
JSONCompact
JSONCompactStrings
JSONEachRow
JSONStringsEachRow
JSONCompactEachRow
JSONCompactStringsEachRow
JSONEachRowWithProgress
JSONStringsEachRowWithProgress
JSONCompactEachRowWithNamesAndTypes
JSONCompactStringsEachRowWithNamesAndTypes
Inserting Data
Selecting Data
Usage of Nested Structures
Native
Null
Pretty
PrettyCompact
PrettyCompactMonoBlock
PrettyNoEscapes
PrettyCompactNoEscapes
PrettySpaceNoEscapes
PrettySpace
RowBinary
RowBinaryWithNamesAndTypes
Values
Vertical
XML
CapnProto
Protobuf
ProtobufSingle
Avro
Data Types Matching
Inserting Data
Selecting Data
AvroConfluent
Data Types Matching
Usage
Parquet
Data Types Matching
Inserting and Selecting Data
Arrow
Data Types Matching
Inserting Data
Selecting Data
ArrowStream
ORC
Data Types Matching
Inserting Data
Selecting Data
LineAsString
Regexp
Format Schema
Skipping Errors
RawBLOB
MsgPack
Data Types Matching
JDBC Driver
ODBC Driver
C++ Client Library
Third-Party Interfaces
Client Libraries from Third-party Developers
Integration Libraries from Third-party Developers
Infrastructure Products
Programming Language Ecosystems
Visual Interfaces from Third-party Developers
Open-Source
Tabix
HouseOps
LightHouse
Redash
Grafana
DBeaver
clickhouse-cli
clickhouse-flamegraph
clickhouse-plantuml
xeus-clickhouse
MindsDB Studio
DBM
Commercial
DataGrip
Yandex DataLens
Holistics Software
Looker
SeekTable
Chadmin
Proxy Servers from Third-party Developers
chproxy
KittenHouse
ClickHouse-Bulk
ClickHouse Engines
Table Engines for Integrations
ODBC
Creating a Table
Usage Example
See Also
JDBC
Creating a Table
Usage Example
See Also
MySQL
Creating a Table
Usage Example
See Also
MongoDB
Creating a Table
Usage Example
HDFS
Usage
Implementation Details
Configuration
Configuration Options
Supported by libhdfs3
ClickHouse extras
Limitations
Kerberos support
HDFS Namenode HA support{#namenode-ha}
Virtual Columns
S3 Table Engine
Create Table
Virtual columns
Implementation Details
Wildcards In Path
Virtual Columns
S3-related settings
Endpoint-based Settings
Usage
See also
SQLite
Creating a Table
Usage Example
Kafka
Creating a Table
Description
Configuration
Kerberos support
Virtual Columns
EmbeddedRocksDB Engine
Creating a Table
Metrics
Configuration
RabbitMQ Engine
Creating a Table
Description
Virtual Columns
PostgreSQL
Creating a Table
Implementation Details
Usage Example
ExternalDistributed
Creating a Table
Implementation Details
MaterializedPostgreSQL
Creating a Table
Requirements
Virtual columns
Table Engines
Engine Families
MergeTree
Log
Integration Engines
Special Engines
Virtual Columns
MergeTree Engine Family
MergeTree
Creating a Table
Query Clauses
Data Storage
Primary Keys and Indexes in Queries
Selecting the Primary Key
Choosing a Primary Key that Differs from the Sorting Key
Use of Indexes and Partitions in Queries
Use of Index for Partially-monotonic Primary Keys
Data Skipping Indexes
Available Types of Indices
Functions Support
Projections
Projection Query
Projection Storage
Query Analysis
Concurrent Data Access
TTL for Columns and Tables
Column TTL
Table TTL
Removing Expired Data
Using Multiple Block Devices for Data Storage
Introduction
Terms
Configuration
Details
Using S3 for Data Storage
Data Replication
Creating Replicated Tables
Recovery After Failures
Recovery After Complete Data Loss
Converting from MergeTree to ReplicatedMergeTree
Converting from ReplicatedMergeTree to MergeTree
Recovery When Metadata in the Zookeeper Cluster Is Lost or Damaged
Custom Partitioning Key
ReplacingMergeTree
Creating a Table
SummingMergeTree
Creating a Table
Usage Example
Data Processing
Common Rules for Summation
The Summation in the Aggregatefunction Columns
Nested Structures
AggregatingMergeTree
Creating a Table
SELECT and INSERT
Example of an Aggregated Materialized View
CollapsingMergeTree
Creating a Table
Collapsing
Data
Algorithm
Example of Use
Example of Another Approach
VersionedCollapsingMergeTree
Creating a Table
Collapsing
Data
Algorithm
Selecting Data
Example of Use
GraphiteMergeTree
Creating a Table
Rollup Configuration
Required Columns
Patterns
Configuration Example
Log Engine Family
Common Properties
Differences
Stripelog
Creating a Table
Writing the Data
Reading the Data
Example of Use
Log
TinyLog
Special Table Engines
Distributed Table Engine
Virtual Columns
Dictionary Table Engine
Example
Merge Table Engine
Examples
Virtual Columns
File Table Engine
Usage in ClickHouse Server
Example
Usage in ClickHouse-local
Details of Implementation
Null Table Engine
Set Table Engine
Limitations and Settings
Join Table Engine
Creating a Table
Specifics and Recommendations
Data Storage
Selecting and Inserting Data
Deleting Data
Limitations and Settings
Usage Examples
URL Table Engine
Usage
Example
Details of Implementation
View Table Engine
MaterializedView Table Engine
Memory Table Engine
Buffer Table Engine
External Data for Query Processing
GenerateRandom Table Engine
Usage in ClickHouse Server
Example
Details of Implementation
Database Engines
[experimental] MaterializedMySQL
Creating a Database
Virtual Columns
Data Types Support
Specifics and Recommendations
Compatibility Restrictions
DDL Queries
Data Replication
Selecting from MaterializedMySQL Tables
Index Conversion
Examples of Use
[experimental] MaterializedPostgreSQL
Creating a Database
Dynamically adding new tables to replication
Dynamically removing tables from replication
Settings
Requirements
Example of Use
Notes
MySQL
Creating a Database
Data Types Support
Global Variables Support
Examples of Use
Lazy
Creating a Database
Atomic
Creating a Database
Specifics and recommendations
Table UUID
RENAME TABLE
DROP/DETACH TABLE
EXCHANGE TABLES/DICTIONARIES
ReplicatedMergeTree in Atomic Database
See Also
SQLite
Creating a Database
Data Types Support
Specifics and Recommendations
Usage Example
PostgreSQL
Creating a Database
Data Types Support
Examples of Use
[experimental] Replicated
Creating a Database
Specifics and Recommendations
Usage Example
SQL Reference
ClickHouse SQL Statements
SELECT Query
Syntax
SELECT Clause
COLUMNS expression
Asterisk
Extreme Values
Notes
Implementation Details
SELECT modifiers
APPLY
EXCEPT
REPLACE
Modifier Combinations
SETTINGS in SELECT Query
ALL Clause
ARRAY JOIN Clause
Basic ARRAY JOIN Examples
Using Aliases
ARRAY JOIN with Nested Data Structure
Implementation Details
DISTINCT Clause
DISTINCT and ORDER BY
Null Processing
Alternatives
FORMAT Clause
Default Format
Implementation Details
FROM Clause
FINAL Modifier
Drawbacks
Implementation Details
GROUP BY Clause
NULL Processing
WITH ROLLUP Modifier
WITH CUBE Modifier
WITH TOTALS Modifier
Configuring Totals Processing
Examples
Implementation Details
GROUP BY Optimization Depending on Table Sorting Key
GROUP BY in External Memory
HAVING Clause
Limitations
INTO OUTFILE Clause
Implementation Details
JOIN Clause
Supported Types of JOIN
Settings
ON Section Conditions
ASOF JOIN Usage
Distributed JOIN
Implicit Type Conversion
Usage Recommendations
Processing of Empty or NULL Cells
Syntax
Syntax Limitations
Performance
Memory Limitations
Examples
LIMIT Clause
LIMIT … WITH TIES Modifier
LIMIT BY Clause
Examples
OFFSET FETCH Clause
Examples
ORDER BY Clause
Sorting of Special Values
Example
Collation Support
Collation Examples
Implementation Details
Optimization of Data Reading
ORDER BY Expr WITH FILL Modifier
PREWHERE Clause
Controlling Prewhere Manually
Limitations
SAMPLE Clause
SAMPLE K
SAMPLE N
SAMPLE K OFFSET M
UNION Clause
WHERE Clause
WITH Clause
Syntax
Examples
INSERT INTO Statement
Constraints
Inserting the Results of SELECT
Performance Considerations
CREATE Queries
CREATE DATABASE
Clauses
IF NOT EXISTS
ON CLUSTER
ENGINE
CREATE TABLE
Syntax Forms
With Explicit Schema
With a Schema Similar to Other Table
From a Table Function
From SELECT query
NULL Or NOT NULL Modifiers
Default Values
DEFAULT
MATERIALIZED
ALIAS
Primary Key
Constraints
TTL Expression
Column Compression Codecs
General Purpose Codecs
Specialized Codecs
Temporary Tables
REPLACE TABLE
Syntax
Examples:
COMMENT Clause
CREATE VIEW
Normal View
Materialized View
Live View [Experimental]
Monitoring Live View Changes
Force Live View Refresh
WITH TIMEOUT Clause
WITH REFRESH Clause
Live View Usage
CREATE DICTIONARY
CREATE FUNCTION
CREATE USER
Identification
User Host
GRANTEES Clause
Examples
CREATE ROLE
Managing Roles
Examples
CREATE ROW POLICY
USING Clause
TO Clause
AS Clause
ON CLUSTER Clause
Examples
CREATE QUOTA
CREATE SETTINGS PROFILE
Example
ALTER
Mutations
Synchronicity of ALTER Queries
Column Manipulations
ADD COLUMN
DROP COLUMN
RENAME COLUMN
CLEAR COLUMN
COMMENT COLUMN
MODIFY COLUMN
MODIFY COLUMN REMOVE
Limitations
Manipulating Partitions and Parts
DETACH PARTITION|PART
DROP PARTITION|PART
DROP DETACHED PARTITION|PART
ATTACH PARTITION|PART
ATTACH PARTITION FROM
REPLACE PARTITION
MOVE PARTITION TO TABLE
CLEAR COLUMN IN PARTITION
FREEZE PARTITION
UNFREEZE PARTITION
CLEAR INDEX IN PARTITION
FETCH PARTITION|PART
MOVE PARTITION|PART
UPDATE IN PARTITION
Example
See Also
DELETE IN PARTITION
Example
See Also
How to Set Partition Expression
Table Settings Manipulations
MODIFY SETTING
RESET SETTING
ALTER TABLE … DELETE Statement
ALTER TABLE … UPDATE Statements
Manipulating Key Expressions
Manipulating Sampling-Key Expressions
Manipulating Data Skipping Indices
Manipulating Constraints
Manipulations with Table TTL
MODIFY TTL
REMOVE TTL
ALTER USER
GRANTEES Clause
Examples
ALTER QUOTA
ALTER ROLE
ALTER ROW POLICY
ALTER SETTINGS PROFILE
Manipulating Projections
ALTER TABLE …
JSONLength(json[, indices_or_keys]…)
JSONType(json[, indices_or_keys]…)
JSONExtractUInt(json[, indices_or_keys]…)
JSONExtractInt(json[, indices_or_keys]…)
JSONExtractFloat(json[, indices_or_keys]…)
JSONExtractBool(json[, indices_or_keys]…)
JSONExtractString(json[, indices_or_keys]…)
JSONExtract(json[, indices_or_keys…], Return_type)
JSONExtractKeysAndValues(json[, indices_or_keys…], Value_type)
JSONExtractRaw(json[, indices_or_keys]…)
JSONExtractArrayRaw(json[, indices_or_keys…])
JSONExtractKeysAndValuesRaw
toJSONString
Functions for Working with External Dictionaries
dictGet, dictGetOrDefault, dictGetOrNull
dictHas
dictGetHierarchy
dictIsIn
dictGetChildren
dictGetDescendant
Other Functions
Functions for Working with Yandex.Metrica Dictionaries
Multiple Geobases
regionToCity(id[, geobase])
regionToArea(id[, geobase])
regionToDistrict(id[, geobase])
regionToCountry(id[, geobase])
regionToContinent(id[, geobase])
regionToTopContinent (#regiontotopcontinent)
regionToPopulation(id[, geobase])
regionIn(lhs, rhs[, geobase])
regionHierarchy(id[, geobase])
regionToName(id[, lang])
Functions for Implementing the IN Operator
in, notIn, globalIn, globalNotIn
arrayJoin function
Functions for Working with Geographical Coordinates
greatCircleDistance
geoDistance
greatCircleAngle
pointInEllipses
pointInPolygon
Functions for Working with Geohash
geohashEncode
geohashDecode
geohashesInBox
Functions for Working with H3 Indexes
h3IsValid
h3GetResolution
h3EdgeAngle
h3EdgeLengthM
geoToH3
h3ToGeo
h3ToGeoBoundary
h3kRing
h3GetBaseCell
h3HexAreaM2
h3IndexesAreNeighbors
h3ToChildren
h3ToParent
h3ToString
stringToH3
h3GetResolution
h3IsResClassIII
h3IsPentagon
h3GetFaces
Functions for Working with Nullable Values
isNull
isNotNull
coalesce
ifNull
nullIf
assumeNotNull
toNullable
Machine Learning Functions
evalMLMethod
stochasticLinearRegression
stochasticLogisticRegression
bayesAB
Introspection Functions
addressToLine
addressToSymbol
demangle
tid
logTrace
Functions for Working with Tuples
tuple
tupleElement
untuple
tupleHammingDistance
Encryption functions
encrypt
aes_encrypt_mysql
decrypt
aes_decrypt_mysql
[experimental] Natural Language Processing functions
stem
lemmatize
synonyms
Other Functions
hostName()
getMacro
FQDN
basename
visibleWidth(x)
toTypeName(x)
blockSize()
byteSize
materialize(x)
ignore(…)
sleep(seconds)
sleepEachRow(seconds)
currentDatabase()
currentUser()
isConstant
isFinite(x)
isInfinite(x)
ifNotFinite
isNaN(x)
hasColumnInTable([‘hostname’[, ‘username’[, ‘password’]],] ‘database’, ‘table’, ‘column’)
bar
transform
transform(x, array_from, array_to, default)
transform(x, array_from, array_to)
formatReadableSize(x)
formatReadableQuantity(x)
formatReadableTimeDelta
least(a, b)
greatest(a, b)
uptime()
version()
blockNumber
rowNumberInBlock
rowNumberInAllBlocks()
neighbor
runningDifference(x)
runningDifferenceStartingWithFirstValue
runningConcurrency
MACNumToString(num)
MACStringToNum(s)
MACStringToOUI(s)
getSizeOfEnumType
blockSerializedSize
toColumnTypeName
dumpColumnStructure
defaultValueOfArgumentType
defaultValueOfTypeName
indexHint
replicate
filesystemAvailable
filesystemFree
filesystemCapacity
initializeAggregation
finalizeAggregation
runningAccumulate
joinGet
modelEvaluate(model_name, …)
throwIf(x[, custom_message])
identity
randomPrintableASCII
randomString
randomFixedString
randomStringUTF8
getSetting
isDecimalOverflow
countDigits
errorCodeToName
tcpPort
currentProfiles
enabledProfiles
defaultProfiles
currentRoles
enabledRoles
defaultRoles
getServerPort
queryID
initialQueryID
Aggregate Functions
NULL Processing
count
min
max
sum
avg
any
stddevPop
stddevSamp
varPop(x)
varSamp
covarPop
List of Aggregate Functions
covarSamp
anyHeavy
anyLast
argMin
argMax
avgWeighted
corr
topK
topKWeighted
groupArray
groupUniqArray
groupArrayInsertAt
groupArrayMovingSum
groupArrayMovingAvg
groupArraySample
groupBitAnd
groupBitOr
groupBitXor
groupBitmap
groupBitmapAnd
groupBitmapOr
groupBitmapXor
sumWithOverflow
deltaSum
See Also
deltaSumTimestamp
sumMap
minMap
maxMap
sumCount
rankCorr
sumKahan
intervalLengthSum
skewPop
skewSamp
kurtPop
kurtSamp
uniq
uniqExact
uniqCombined
uniqCombined64
uniqHLL12
uniqTheta
quantile
quantiles Functions
quantiles
quantilesExactExclusive
quantilesExactInclusive
quantileExact Functions
quantileExact
quantileExactLow
quantileExactHigh
quantileExactExclusive
quantileExactInclusive
quantileExactWeighted
quantileTiming
quantileTimingWeighted
quantilesTimingWeighted
quantileDeterministic
quantileTDigest
quantileTDigestWeighted
quantileBFloat16
quantileBFloat16Weighted
median
simpleLinearRegression
stochasticLinearRegression
Parameters
Usage
Notes
stochasticLogisticRegression
Parameters
categoricalInformationValue
studentTTest
welchTTest
mannWhitneyUTest
Aggregate Function Combinators
-If
-Array
-SimpleState
-State
-Merge
-MergeState
-ForEach
-Distinct
-OrDefault
-OrNull
-Resample
Parametric Aggregate Functions
histogram
sequenceMatch(pattern)(timestamp, cond1, cond2, …)
sequenceCount(pattern)(time, cond1, cond2, …)
windowFunnel
retention
uniqUpTo(N)(x)
sumMapFiltered(keys_to_keep)(keys, values)
sequenceNextNode
Table Functions
file
Globs in Path
Virtual Columns
merge
numbers
remote, remoteSecure
Globs in Addresses
url
Globs in URL
mysql
postgresql
Implementation Details
jdbc
odbc
Usage Example
See Also
hdfs
Virtual Columns
s3 Table Function
Usage
Partitioned Write
input
generateRandom
Usage Example
cluster, clusterAllReplicas
view
null
dictionary
s3Cluster Table Function
sqlite
Dictionaries
External Dictionaries
See Also
Configuring an External Dictionary
Storing Dictionaries in Memory
Ways to Store Dictionaries in Memory
flat
hashed
sparse_hashed
complex_key_hashed
range_hashed
complex_key_range_hashed
cache
complex_key_cache
ssd_cache
complex_key_ssd_cache
direct
complex_key_direct
ip_trie
Dictionary Updates
Sources of External Dictionaries
Local File
Executable File
Executable Pool
Http(s)
ODBC
Known Vulnerability of the ODBC Dictionary Functionality
Example of Connecting Postgresql
Example of Connecting MS SQL Server
DBMS
Mysql
ClickHouse
Mongodb
Redis
Cassandra
PosgreSQL
Dictionary Key and Fields
Key
Numeric Key
Composite Key
Attributes
Hierarchical Dictionaries
Polygon dictionaries
Internal Dictionaries
Data Types
UInt8, UInt16, UInt32, UInt64, UInt256, Int8, Int16, Int32, Int64, Int128, Int256
Int Ranges
UInt Ranges
Float32, Float64
Using Floating-point Numbers
NaN and Inf
Decimal(P, S), Decimal32(S), Decimal64(S), Decimal128(S), Decimal256(S)
Parameters
Decimal Value Ranges
Internal Representation
Operations and Result Type
Overflow Checks
Boolean Values
String
Encodings
Fixedstring
UUID
How to Generate
Usage Example
Restrictions
Date
Date32
Datetime
Usage Remarks
Examples
Limitations on timezones support
See Also
Datetime64
Examples
Enum
Usage Examples
General Rules and Usage
LowCardinality Data Type
Syntax
Description
Example
Related Settings and Functions
See Also
Array(t)
Creating an Array
Working with Data Types
Array Size
AggregateFunction
Usage
Data Insertion
Data Selection
Usage Example
Nested Data Structures
Nested
Nested(name1 Type1, Name2 Type2, …)
Tuple(t1, T2, …)
Creating a Tuple
Working with Data Types
Addressing Tuple Elements
Nullable(typename)
Storage Features
Finding NULL
Usage Example
Special Data Types
Expression
Set
Nothing
Interval
Usage Remarks
See Also
Domains
Extra Features of Domains
Limitations
IPv4
Basic Usage
IPv6
Basic Usage
Multiword Types
Multiword Types Support
Geo Data Types
Point
Ring
Polygon
MultiPolygon
Map(key, value)
Convert Tuple to Map Type
Map.keys and Map.values Subcolumns
SimpleAggregateFunction
Operators
Access Operators
Numeric Negation Operator
Multiplication and Division Operators
Addition and Subtraction Operators
Comparison Operators
Operators for Working with Data Sets
Operators for Working with Dates and Times
EXTRACT
INTERVAL
Logical AND Operator
Logical OR Operator
Logical Negation Operator
Conditional Operator
Conditional Expression
Concatenation Operator
Lambda Creation Operator
Array Creation Operator
Tuple Creation Operator
Associativity
Checking for NULL
IS NULL
IS NOT NULL
IN Operators
NULL Processing
Distributed Subqueries
Distributed Subqueries and max_parallel_replicas
ANSI SQL Compatibility of ClickHouse SQL Dialect
Differences in Behaviour
Feature Status
[experimental] Window Functions
References
GitHub Issues
Tests
Postgres Docs
MySQL Docs
ClickHouse Guides
Applying a Catboost Model in ClickHouse
Prerequisites
1. Create a Table
2. Insert the Data to the Table
3. Integrate CatBoost into ClickHouse
4. Run the Model Inference from SQL
Operations
Requirements
CPU
RAM
Swap File
Storage Subsystem
Network
Software
Monitoring
Resource Utilization
ClickHouse Server Metrics
Troubleshooting
Installation
You Cannot Get Deb Packages from ClickHouse Repository with Apt-get
Connecting to the Server
Server Is Not Running
Configuration Parameters
Query Processing
Efficiency of Query Processing
ClickHouse Upgrade
Access Control and Account Management
Usage
Properties of Current Solution
User Account
Settings Applying
Role
Row Policy
Settings Profile
Quota
Enabling SQL-driven Access Control and Account Management
External User Authenticators and Directories
Kerberos
Enabling Kerberos in ClickHouse
Parameters:
Kerberos as an external authenticator for existing users
Enabling Kerberos in users.xml
Enabling Kerberos using SQL
LDAP
LDAP Server Definition
LDAP External Authenticator
LDAP Exernal User Directory
Data Backup
Duplicating Source Data Somewhere Else
Filesystem Snapshots
clickhouse-copier
Manipulations with Parts
Configuration Files
Override
Substitution
User Settings
XML example
YAML examples
Implementation Details
Quotas
Optimizing Performance
Sampling Query Profiler
Example
System Tables
Introduction
Sources of System Metrics
system.asynchronous_metric_log
system.asynchronous_metrics
system.clusters
system.columns
system.contributors
system.crash_log
system.current_roles
system.data_skipping_indices
system.data_type_families
system.databases
system.detached_parts
system.dictionaries
system.disks
system.distributed_ddl_queue
system.distribution_queue
system.enabled_roles
system.errors
system.events
system.functions
system.grants
system.graphite_retentions
system.licenses
system.merge_tree_settings
system.merges
system.metric_log
system.metrics
system.mutations
system.numbers
system.numbers_mt
system.one
system.opentelemetry_span_log
system.part_log
system.parts
system.parts_columns
system.processes
system.query_log
system.query_thread_log
system.query_views_log
system.quota_limits
system.quota_usage
See Also
system.quotas
See Also
system.quotas_usage
See Also
system.replicas
system.replicated_fetches
system.replication_queue
system.role_grants
system.roles
See Also
system.row_policies
See Also
system.settings
system.settings_profile_elements
system.settings_profiles
See Also
system.stack_trace
system.storage_policies
system.table_engines
system.tables
system.text_log
system.time_zones
system.trace_log
system.users
See Also
system.zookeeper
system.zookeeper_log
Server Configuration Parameters
Server Settings
builtin_dictionaries_reload_interval
compression
encryption
custom_settings_prefixes
core_dump
database_atomic_delay_before_drop_table_sec
default_database
default_profile
default_replica_path
default_replica_name
dictionaries_config
dictionaries_lazy_load
format_schema_path
graphite
graphite_rollup
http_port/https_port
http_server_default_response
include_from
interserver_http_port
interserver_http_host
interserver_https_port
interserver_https_host
interserver_http_credentials
keep_alive_timeout
listen_host
logger
send_crash_reports
macros
mark_cache_size
max_server_memory_usage
max_server_memory_usage_to_ram_ratio
max_concurrent_queries
max_concurrent_queries_for_all_users
min_marks_to_honor_max_concurrent_queries
max_connections
max_open_files
max_table_size_to_drop
max_thread_pool_size
merge_tree
metric_log
replicated_merge_tree
openSSL
part_log
path
prometheus
query_log
query_thread_log
query_views_log
text_log
trace_log
query_masking_rules
remote_servers
timezone
tcp_port
tcp_port_secure
mysql_port
tmp_path
tmp_policy
uncompressed_cache_size
user_files_path
users_config
zookeeper
use_minimalistic_part_header_in_zookeeper
disable_internal_dns_cache
dns_cache_update_period
distributed_ddl
access_control_path
user_directories
How to Test Your Hardware with ClickHouse
Automated Run
Manual Run
Settings
Custom Settings
Permissions for Queries
readonly
allow_ddl
Restrictions on Query Complexity
max_memory_usage
max_memory_usage_for_user
max_rows_to_read
max_bytes_to_read
read_overflow_mode
max_rows_to_read_leaf
max_bytes_to_read_leaf
read_overflow_mode_leaf
max_rows_to_group_by
group_by_overflow_mode
max_bytes_before_external_group_by
max_rows_to_sort
max_bytes_to_sort
sort_overflow_mode
max_result_rows
max_result_bytes
result_overflow_mode
max_execution_time
timeout_overflow_mode
min_execution_speed
min_execution_speed_bytes
max_execution_speed
max_execution_speed_bytes
timeout_before_checking_execution_speed
max_columns_to_read
max_temporary_columns
max_temporary_non_const_columns
max_subquery_depth
max_pipeline_depth
max_ast_depth
max_ast_elements
max_rows_in_set
max_bytes_in_set
set_overflow_mode
max_rows_in_distinct
max_bytes_in_distinct
distinct_overflow_mode
max_rows_to_transfer
max_bytes_to_transfer
transfer_overflow_mode
max_rows_in_join
max_bytes_in_join
join_overflow_mode
max_partitions_per_insert_block
Settings Profiles
Constraints on Settings
User Settings
user_name/password
access_management
user_name/networks
user_name/profile
user_name/quota
user_name/databases
MergeTree tables settings
parts_to_throw_insert
parts_to_delay_insert
inactive_parts_to_throw_insert
inactive_parts_to_delay_insert
max_delay_to_insert
max_parts_in_total
replicated_deduplication_window
non_replicated_deduplication_window
replicated_deduplication_window_seconds
replicated_fetches_http_connection_timeout
replicated_fetches_http_send_timeout
replicated_fetches_http_receive_timeout
max_replicated_fetches_network_bandwidth
max_replicated_sends_network_bandwidth
old_parts_lifetime
max_bytes_to_merge_at_max_space_in_pool
max_bytes_to_merge_at_min_space_in_pool
merge_max_block_size
max_part_loading_threads
max_partitions_to_read
allow_floating_point_partition_key
check_sample_column_is_correct
Settings
distributed_product_mode
prefer_global_in_and_join
enable_optimize_predicate_expression
fallback_to_stale_replicas_for_distributed_queries
force_index_by_date
force_primary_key
use_skip_indexes
force_data_skipping_indices
format_schema
fsync_metadata
function_range_max_elements_in_block
enable_http_compression
http_zlib_compression_level
http_native_compression_disable_checksumming_on_decompress
http_max_uri_size
table_function_remote_max_addresses
glob_expansion_max_elements
send_progress_in_http_headers
max_http_get_redirects
input_format_allow_errors_num
input_format_allow_errors_ratio
input_format_parquet_import_nested
input_format_arrow_import_nested
input_format_orc_import_nested
input_format_values_interpret_expressions
input_format_values_deduce_templates_of_expressions
input_format_values_accurate_types_of_literals
input_format_defaults_for_omitted_fields
input_format_tsv_empty_as_default
input_format_tsv_enum_as_number
input_format_null_as_default
insert_null_as_default
input_format_skip_unknown_fields
input_format_import_nested_json
input_format_with_names_use_header
date_time_input_format
date_time_output_format
join_default_strictness
join_algorithm
join_any_take_last_row
join_use_nulls
partial_merge_join_optimizations
partial_merge_join_rows_in_right_blocks
join_on_disk_max_files_to_merge
any_join_distinct_right_table_keys
temporary_files_codec
max_block_size
preferred_block_size_bytes
merge_tree_min_rows_for_concurrent_read
merge_tree_min_bytes_for_concurrent_read
merge_tree_min_rows_for_seek
merge_tree_min_bytes_for_seek
merge_tree_coarse_index_granularity
merge_tree_max_rows_to_use_cache
merge_tree_max_bytes_to_use_cache
merge_tree_clear_old_temporary_directories_interval_seconds
merge_tree_clear_old_parts_interval_seconds
min_bytes_to_use_direct_io
network_compression_method
network_zstd_compression_level
log_queries
log_queries_min_query_duration_ms
log_queries_min_type
log_query_threads
log_query_views
log_comment
max_insert_block_size
min_insert_block_size_rows
min_insert_block_size_bytes
max_replica_delay_for_distributed_queries
max_threads
max_insert_threads
max_compress_block_size
min_compress_block_size
max_query_size
max_parser_depth
interactive_delay
connect_timeout, receive_timeout, send_timeout
cancel_http_readonly_queries_on_client_close
poll_interval
max_distributed_connections
distributed_connections_pool_size
max_distributed_depth
max_replicated_fetches_network_bandwidth_for_server
max_replicated_sends_network_bandwidth_for_server
connect_timeout_with_failover_ms
connection_pool_max_wait_ms
connections_with_failover_max_tries
extremes
kafka_max_wait_ms
use_uncompressed_cache
replace_running_query
replace_running_query_max_wait_ms
stream_flush_interval_ms
load_balancing
Random (by Default)
Nearest Hostname
In Order
First or Random
Round Robin
prefer_localhost_replica
totals_mode
totals_auto_threshold
max_parallel_replicas
compile_expressions
min_count_to_compile_expression
output_format_json_quote_64bit_integers
output_format_json_quote_denormals
format_csv_delimiter
input_format_csv_unquoted_null_literal_as_null
input_format_csv_enum_as_number
output_format_csv_crlf_end_of_line
output_format_tsv_crlf_end_of_line
insert_quorum
insert_quorum_timeout
select_sequential_consistency
insert_deduplicate
deduplicate_blocks_in_dependent_materialized_views
max_network_bytes
max_network_bandwidth
max_network_bandwidth_for_user
max_network_bandwidth_for_all_users
count_distinct_implementation
skip_unavailable_shards
distributed_group_by_no_merge
distributed_push_down_limit (#distributed-push-down-limit}
optimize_skip_unused_shards_limit
optimize_skip_unused_shards
optimize_skip_unused_shards_rewrite_in
allow_nondeterministic_optimize_skip_unused_shards
optimize_skip_unused_shards_nesting
force_optimize_skip_unused_shards
force_optimize_skip_unused_shards_nesting
optimize_distributed_group_by_sharding_key
optimize_throw_if_noop
optimize_functions_to_subcolumns
distributed_replica_error_half_life
distributed_replica_error_cap
distributed_replica_max_ignored_errors
distributed_directory_monitor_sleep_time_ms
distributed_directory_monitor_max_sleep_time_ms
distributed_directory_monitor_batch_inserts
distributed_directory_monitor_split_batch_on_failure
os_thread_priority
query_profiler_real_time_period_ns
query_profiler_cpu_time_period_ns
allow_introspection_functions
input_format_parallel_parsing
output_format_parallel_formatting
min_chunk_bytes_for_parallel_parsing
output_format_avro_codec
output_format_avro_sync_interval
output_format_avro_string_column_pattern
format_avro_schema_registry_url
input_format_avro_allow_missing_fields
background_pool_size
merge_selecting_sleep_ms
parallel_distributed_insert_select
insert_distributed_sync
insert_distributed_one_random_shard
insert_shard_id
use_compact_format_in_distributed_parts_names
background_buffer_flush_schedule_pool_size
background_move_pool_size
background_schedule_pool_size
background_fetches_pool_size
always_fetch_merged_part
background_distributed_schedule_pool_size
background_message_broker_schedule_pool_size
validate_polygons
transform_null_in
low_cardinality_max_dictionary_size
low_cardinality_use_single_dictionary_for_part
low_cardinality_allow_in_native_format
allow_suspicious_low_cardinality_types
min_insert_block_size_rows_for_materialized_views
min_insert_block_size_bytes_for_materialized_views
output_format_pretty_grid_charset
optimize_read_in_order
optimize_aggregation_in_order
mutations_sync
ttl_only_drop_parts
lock_acquire_timeout
cast_keep_nullable
output_format_pretty_max_value_width
output_format_pretty_row_numbers
system_events_show_zero_values
persistent
output_format_csv_null_representation
output_format_tsv_null_representation
output_format_json_array_of_rows
allow_nullable_key
aggregate_functions_null_for_empty
union_default_mode
data_type_default_nullable
execute_merges_on_single_replica_time_threshold
max_final_threads
opentelemetry_start_trace_probability
optimize_on_insert
engine_file_empty_if_not_exists
engine_file_truncate_on_insert
allow_experimental_geo_types
database_atomic_wait_for_drop_and_detach_synchronously
show_table_uuid_in_table_create_query_if_not_nil
allow_experimental_live_view
live_view_heartbeat_interval
max_live_view_insert_blocks_before_refresh
temporary_live_view_timeout
periodic_live_view_refresh
http_connection_timeout
http_send_timeout
http_receive_timeout
check_query_single_value_result
prefer_column_name_to_alias
limit
offset
optimize_syntax_fuse_functions
allow_experimental_database_replicated
database_replicated_initial_query_timeout_sec
distributed_ddl_task_timeout
distributed_ddl_output_mode
flatten_nested
external_table_functions_use_nulls
output_format_arrow_low_cardinality_as_dictionary
materialized_postgresql_max_block_size
materialized_postgresql_tables_list
materialized_postgresql_allow_automatic_update
materialized_postgresql_replication_slot
materialized_postgresql_replication_slot
allow_experimental_projection_optimization
force_optimize_projection
replication_alter_partitions_sync
replication_wait_for_inactive_replica_timeout
regexp_max_matches_per_row
log_queries_probability
short_circuit_function_evaluation
max_hyperscan_regexp_length
max_hyperscan_regexp_total_length
ClickHouse Utility
clickhouse-copier
Running Clickhouse-copier
Format of Zookeeper.xml
Configuration of Copying Tasks
clickhouse-local
Usage
Examples
clickhouse-benchmark
Keys
Output
Comparison Mode
Example
clickhouse-format
Examples
ClickHouse compressor
Examples
ClickHouse obfuscator
clickhouse-odbc-bridge
Usage
Example:
Usage Recommendations
CPU Scaling Governor
CPU Limitations
RAM
Storage Subsystem
RAID
File System
Linux Kernel
Network
Huge Pages
Hypervisor configuration
ZooKeeper
[experimental] OpenTelemetry Support
Supplying Trace Context to ClickHouse
Propagating the Trace Context
Tracing the ClickHouse Itself
Integration with monitoring systems
Cache Types
[pre-production] ClickHouse Keeper
Implementation details
Configuration
How to run
[experimental] Migration from ZooKeeper
External Disks for Storing Data
Zero-copy Replication
Configuring HDFS
Using Virtual File System for Data Encryption
ClickHouse Development
The Beginner ClickHouse Developer Instruction
Creating a Repository on GitHub
Cloning a Repository to Your Development Machine
Working with Submodules
Build System
Optional External Libraries
C++ Compiler
The Building Process
Running the Built Executable of ClickHouse
IDE (Integrated Development Environment)
Writing Code
Test Data
Creating Pull Request
Overview of ClickHouse Architecture
Columns
Field
Leaky Abstractions
Data Types
Block
Block Streams
Formats
I/O
Tables
Parsers
Interpreters
Functions
Aggregate Functions
Server
Distributed Query Execution
Merge Tree
Replication
Continuous Integration Checks
Merge With Master
Docs check
Report Details
Description Check
Push To Dockerhub
Marker Check
Style Check
Report Details
PVS Check
Report Details
Fast Test
Report Details
Status Page Files
Status Page Columns
Build Check
Report Details
Special Build Check
Functional Stateless Tests
Functional Stateful Tests
Integration Tests
Testflows Check
Stress Test
Split Build Smoke Test
Compatibility Check
AST Fuzzer
Performance Tests
QA
How to Build ClickHouse on Linux
Normal Build for Development on Ubuntu
Install Git, CMake, Python and Ninja
Install clang-13 (recommended)
Use clang-13 for Builds
Checkout ClickHouse Sources
Build ClickHouse
How to Build ClickHouse on Any Linux
How to Build ClickHouse Debian Package
Install Git
Checkout ClickHouse Sources
Run Release Script
Faster builds for development
You Don’t Have to Build ClickHouse
Split build configuration
How to Build ClickHouse on Mac OS X
Install Homebrew
Install Xcode and Command Line Tools
Install Required Compilers, Tools, and Libraries
Checkout ClickHouse Sources
Build ClickHouse
Caveats
Run ClickHouse server:
How to Build ClickHouse on Linux for Mac OS X
Install Clang-8
Install Cross-Compilation Toolset
Build ClickHouse
How to Build ClickHouse on Linux for AARCH64 (ARM64) Architecture
Install Clang-8
Install Cross-Compilation Toolset
Build ClickHouse
How to Write C++ Code
General Recommendations
Formatting
Comments
Names
How to Write Code
Unused Features of C++
Platform
Tools
Libraries
General Recommendations
Additional Recommendations
ClickHouse Testing
Functional Tests
Running a Test Locally
Adding a New Test
Choosing the Test Name
Checking for an Error that Must Occur
Testing a Distributed Query
Known Bugs
Integration Tests
Unit Tests
Performance Tests
Test Tools and Scripts
Miscellaneous Tests
Manual Testing
Testing Environment
Load Testing
Build Tests
Testing for Protocol Compatibility
Help from the Compiler
Sanitizers
Address sanitizer
Thread sanitizer
Memory sanitizer
Undefined behaviour sanitizer
Valgrind (Memcheck)
Fuzzing
Stress test
Thread Fuzzer
Security Audit
Static Analyzers
Hardening
Runtime Integrity Checks
Code Style
Metrica B2B Tests
Test Coverage
Tests for Tests
Testflows
Yandex Checks (only for Yandex employees)
Test Automation
Third-Party Libraries Used
Guidelines for adding new third-party libraries and maintaining custom changes in them
Browse ClickHouse Source Code
CMake in ClickHouse
TL; DR How to make ClickHouse compile and link faster?
CMake files types
List of CMake flags
ClickHouse modes
External libraries
External libraries system/bundled mode
Other flags
Developer's guide for adding new CMake options
Don't be obvious. Be informative.
If the option's state could produce unwanted (or unusual) result, explicitly warn the user.
In the option's description, explain WHAT the option does rather than WHY it does something.
Don't assume other developers know as much as you do.
Prefer consistent default values.
How to add test queries to ClickHouse CI
Why adding tests
Steps to do
Prerequisite
Preparation
New branch for the test
Install & run clickhouse
Creating the test file
How to create a good test
Test naming rules
Commit / push / create PR.
ClickHouse Cloud Service
ClickHouse Commercial Support Service
ClickHouse Commercial Services
General Questions About ClickHouse
Why ClickHouse Is So Fast?
Who Is Using ClickHouse?
What Does “ClickHouse” Mean?
What Does “Не тормозит” Mean?
What Is OLAP?
OLAP from the Business Perspective
OLAP from the Technical Perspective
What Is a Columnar Database?
Why Not Use Something Like MapReduce?
Questions About ClickHouse Use Cases
Can I Use ClickHouse As a Key-Value Storage?
Can I Use ClickHouse As a Time-Series Database?
Question About Operating ClickHouse Servers and Clusters
Which ClickHouse Version to Use in Production?
Which ClickHouse Version Do You Recommend?
How to Choose Between ClickHouse Releases?
Is It Possible to Delete Old Records from a ClickHouse Table?
TTL
ALTER DELETE
DROP PARTITION
TRUNCATE
Questions About Integrating ClickHouse and Other Systems
How Do I Export Data from ClickHouse to a File?
Using INTO OUTFILE Clause
Using a File-Engine Table
Using Command-Line Redirection
How to Import JSON Into ClickHouse?
Examples
Useful Settings
What If I Have a Problem with Encodings When Using Oracle Via ODBC?
ClickHouse F.A.Q
ClickHouse release v21.9, 2021-09-09
Backward Incompatible Change
New Feature
Experimental Feature
Performance Improvement
Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v21.8, 2021-08-12
Upgrade Notes
New Features
Performance Improvements
Improvements
Bug Fixes
ClickHouse release v21.7, 2021-07-09
Backward Incompatible Change
New Feature
Experimental Feature
Performance Improvement
Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release 21.6, 2021-06-05
Upgrade Notes
New Feature
Experimental Feature
Performance Improvement
Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release 21.5, 2021-05-20
Backward Incompatible Change
New Feature
Performance Improvement
Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release 21.4
ClickHouse release 21.4.1 2021-04-12
Backward Incompatible Change
New Feature
Experimental Feature
Performance Improvement
Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release 21.3 (LTS)
ClickHouse release v21.3, 2021-03-12
Backward Incompatible Change
New Feature
Experimental feature
Performance Improvement
Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release 21.2
ClickHouse release v<IP_ADDRESS>-stable, 2021-02-07
Backward Incompatible Change
New Feature
Performance Improvement
Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release 21.1
ClickHouse release v<IP_ADDRESS>-stable, 2021-02-03
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable 2021-01-18
Backward Incompatible Change
New Feature
Experimental Feature
Performance Improvement
Improvement
Bug Fix
Build/Testing/Packaging Improvement
Changelog for 2020
ClickHouse release 20.12
ClickHouse release v<IP_ADDRESS>-stable, 2020-12-28
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-stable, 2020-12-24
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable, 2020-12-13
Backward Incompatible Change
New Feature
Bug Fix
Improvement
Performance Improvement
Experimental Feature
Build/Testing/Packaging Improvement
ClickHouse release 20.11
ClickHouse release v<IP_ADDRESS>-stable, 2021-03-02
Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-stable, 2020-12-24
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable, 2020-11-13
Bug Fix
ClickHouse release v<IP_ADDRESS>, 2020-11-11
Backward Incompatible Change
New Feature
Experimental Feature
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release 20.10
ClickHouse release v<IP_ADDRESS>-stable, 2020-12-24
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable, 2020-11-13
Bug Fix
Improvement
ClickHouse release v<IP_ADDRESS>, 2020-10-28
Backward Incompatible Change
New Feature
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release 20.9
ClickHouse release v<IP_ADDRESS>-stable, 2020-12-07
Performance Improvement
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-stable, 2020-11-20
Improvement
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable, 2020-11-13
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable (2020-10-29)
Bug Fix
Improvement
ClickHouse release v<IP_ADDRESS>-stable (2020-10-09)
Bug Fix
Improvement
ClickHouse release v<IP_ADDRESS>, 2020-09-22
Backward Incompatible Change
New Feature
Bug Fix
Experimental Feature
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release 20.8
ClickHouse release v<IP_ADDRESS>-lts, 2021-01-16
Bug Fix
ClickHouse release v<IP_ADDRESS>-lts, 2020-12-25
Bug Fix
ClickHouse release v<IP_ADDRESS>-lts, 2020-12-24
Bug Fix
ClickHouse release v<IP_ADDRESS>-lts, 2020-11-13
Bug Fix
ClickHouse release v<IP_ADDRESS>-lts, 2020-10-29
Bug Fix
Improvement
ClickHouse release v<IP_ADDRESS>-lts, 2020-10-09
Bug Fix
Improvement
ClickHouse release v<IP_ADDRESS>-stable, 2020-09-18
Bug Fix
Improvement
ClickHouse release v<IP_ADDRESS>-stable, 2020-09-08
Backward Incompatible Change
New Feature
Bug Fix
Improvement
Performance Improvement
Experimental Feature
Build/Testing/Packaging Improvement
ClickHouse release 20.7
ClickHouse release v<IP_ADDRESS>-stable, 2020-08-31
Backward Incompatible Change
New Feature
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release 20.6
ClickHouse release v<IP_ADDRESS>-stable
Backward Incompatible Change
New Feature
Bug Fix
Improvement
Performance Improvement
Experimental Feature
Build/Testing/Packaging Improvement
ClickHouse release 20.5
ClickHouse release v<IP_ADDRESS>-stable 2020-08-10
Bug Fix
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-stable 2020-07-02
Backward Incompatible Change
New Feature
Bug Fix
Improvement
Performance Improvement
Experimental Feature
Build/Testing/Packaging Improvement
ClickHouse release v20.4
ClickHouse release v<IP_ADDRESS>-stable 2020-08-10
Bug Fix
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-stable 2020-06-25
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-stable 2020-06-10
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-stable 2020-05-26
ClickHouse release v<IP_ADDRESS>-stable 2020-05-23
Bug Fix
ClickHouse release v<IP_ADDRESS>, 2020-05-12
Backward Incompatible Change
New Feature
Experimental Feature
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release v20.3
ClickHouse release v<IP_ADDRESS>-lts, 2020-11-02
Bug Fix
ClickHouse release v<IP_ADDRESS>-lts, 2020-10-09
Bug Fix
ClickHouse release v<IP_ADDRESS>-lts, 2020-09-18
Bug Fix
Improvement
ClickHouse release v<IP_ADDRESS>-lts, 2020-09-08
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-lts, 2020-08-15
Bug Fix
ClickHouse release v<IP_ADDRESS>-lts 2020-08-10
Bug Fix
Performance Improvement
ClickHouse release v<IP_ADDRESS>-lts 2020-06-25
Bug Fix
ClickHouse release v<IP_ADDRESS>-lts 2020-06-10
New Feature
Bug Fix
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>-lts 2020-05-23
Bug Fix
Build/Testing/Packaging Improvement
Bug fix
ClickHouse release v<IP_ADDRESS>, 2020-04-23
Bug Fix
Performance Improvement
ClickHouse release v<IP_ADDRESS>, 2020-04-17
Bug Fix
ClickHouse release v<IP_ADDRESS>, 2020-04-16
New Feature
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>, 2020-03-27
Bug Fix
Improvement
ClickHouse release v<IP_ADDRESS>, 2020-03-20
Bug Fix
ClickHouse release v<IP_ADDRESS>, 2020-03-17
Bug Fix
ClickHouse release v<IP_ADDRESS>, 2020-03-12
Backward Incompatible Change
New Feature
Experimental Feature
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse release v20.1
ClickHouse release v<IP_ADDRESS>-stable 2020-60-26
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable 2020-06-19
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable 2020-06-11
Bug Fix
ClickHouse release v<IP_ADDRESS>-stable 2020-06-10
Bug Fix
ClickHouse release v<IP_ADDRESS>, 2020-05-26
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>, 2020-04-17
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>, 2020-03-28
Bug Fix
Improvement
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>, 2020-03-20
Bug Fix
ClickHouse release v<IP_ADDRESS>, 2020-03-18
Bug Fix
Build/Testing/Packaging Improvement
ClickHouse release v<IP_ADDRESS>, 2020-03-05
Bug Fix
New Feature
ClickHouse release v<IP_ADDRESS>, 2020-01-22
Backward Incompatible Change
New Feature
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
Experimental Feature
Security Fix
Changelog for 2019
ClickHouse Release 19.17
ClickHouse Release <IP_ADDRESS>, 2019-12-27
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-11-22
Backward Incompatible Change
New Feature
Experimental Feature
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
Other
ClickHouse Release 19.16
ClickHouse Release <IP_ADDRESS>, 2020-03-25
ClickHouse Release <IP_ADDRESS>, 2020-03-05
New Feature
ClickHouse Release <IP_ADDRESS>, 2019-10-30
Backward Incompatible Change
New Feature
Bug Fix
Improvement
Performance Improvement
Build/Testing/Packaging Improvement
Code Cleanup
ClickHouse Release 19.15
ClickHouse Release <IP_ADDRESS>, 2019-10-31
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-10-09
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-10-01
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ClickHouse Release 19.14
ClickHouse Release <IP_ADDRESS>, 2019-10-02
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ClickHouse Release <IP_ADDRESS>, 2019-09-19
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ClickHouse Release <IP_ADDRESS>, 2019-09-10
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ClickHouse Release 19.13
ClickHouse Release <IP_ADDRESS>, 2019-10-02
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ClickHouse Release <IP_ADDRESS>, 2019-09-20
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-09-10
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ClickHouse Release <IP_ADDRESS>, 2019-08-22
Bug Fix
Security Fix
ClickHouse Release <IP_ADDRESS>, 2019-08-14
New Feature
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ClickHouse Release 19.11
ClickHouse Release <IP_ADDRESS>, 2019-11-01
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-10-02
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-09-13
ClickHouse Release <IP_ADDRESS>, 2019-09-10
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-09-6
Security Fix
ClickHouse Release <IP_ADDRESS>, 2019-08-22
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-08-14
Bug Fix
Improvement
ClickHouse Release <IP_ADDRESS>, 2019-08-05
Bug Fix
Backward Incompatible Change
ClickHouse Release <IP_ADDRESS>, 2019-08-01
Bug Fix
Build/Testing/Packaging Improvement
Backward Incompatible Change
ClickHouse Release <IP_ADDRESS>, 2019-07-18
New Feature
Bug Fix
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Performance Improvement
Build/Testing/Packaging Improvement
Backward Incompatible Change
ClickHouse Release 19.10
ClickHouse Release <IP_ADDRESS>, 2019-07-12
New Feature
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Build/Testing/Packaging Improvement
ClickHouse Release 19.9
ClickHouse Release <IP_ADDRESS>, 2019-07-05
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-06-24
New Feature
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Bug Fix
Build/Testing/Packaging Improvement
ClickHouse Release 19.8
ClickHouse Release <IP_ADDRESS>, 2019-06-11
New Features
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Performance Improvements
Bug Fixes
Documentation
Build/Testing/Packaging Improvements
ClickHouse Release 19.7
ClickHouse Release <IP_ADDRESS>, 2019-07-05
Bug Fix
ClickHouse Release <IP_ADDRESS>, 2019-06-09
New Features
Bug Fixes
ClickHouse Release <IP_ADDRESS>, 2019-05-30
New Features
Bug Fixes
Performance Improvements
Documentation
Build/Testing/Packaging Improvements
ClickHouse Release 19.6
ClickHouse Release <IP_ADDRESS>, 2019-06-13
Bug Fixes
ClickHouse Release <IP_ADDRESS>, 2019-05-13
New Features
Experimental Features
Improvements
Performance Improvements
Backward Incompatible Changes
Bug Fixes
Build/Testing/Packaging Improvements
ClickHouse Release 19.5
ClickHouse Release <IP_ADDRESS>, 2019-05-13
Bug Fixes
ClickHouse Release <IP_ADDRESS>, 2019-04-18
Bug Fixes
ClickHouse Release <IP_ADDRESS>, 2019-04-15
New Features
Improvement
Bug Fix
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Performance Improvement
Build/Testing/Packaging Improvement
ClickHouse Release 19.4
ClickHouse Release <IP_ADDRESS>, 2019-04-17
Bug Fixes
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ClickHouse Release <IP_ADDRESS>, 2019-04-02
Bug Fixes
Build/Testing/Packaging Improvement
ClickHouse Release <IP_ADDRESS>, 2019-03-30
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ClickHouse Release <IP_ADDRESS>, 2019-03-19
Bug Fixes
ClickHouse Release <IP_ADDRESS>, 2019-03-09
New Features
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Improvements
Performance Improvements
Build/Testing/Packaging Improvement
ClickHouse Release 19.3
ClickHouse Release <IP_ADDRESS>, 2019-04-02
Bug Fixes
Build/Testing/Packaging Improvement
ClickHouse Release 19.3.7, 2019-03-12
Bug Fixes
ClickHouse Release 19.3.6, 2019-03-02
Bug Fixes
Build/Testing/Packaging Improvements
ClickHouse Release 19.3.5, 2019-02-21
Bug Fixes
ClickHouse Release 19.3.4, 2019-02-16
Improvements
Bug Fixes
Build/Testing/Packaging Improvements
ClickHouse Release 19.3.3, 2019-02-13
New Features
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Performance Improvements
Improvements
ClickHouse Release 19.1
ClickHouse Release 19.1.14, 2019-03-14
ClickHouse Release 19.1.13, 2019-03-12
ClickHouse Release 19.1.10, 2019-03-03
ClickHouse Release 19.1
ClickHouse Release 19.1.9, 2019-02-21
Bug Fixes
ClickHouse Release 19.1.8, 2019-02-16
Bug Fixes
ClickHouse Release 19.1
ClickHouse Release 19.1.7, 2019-02-15
Bug Fixes
ClickHouse Release 19.1.6, 2019-01-24
New Features
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Performance Improvements
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Build/Testing/Packaging Improvements
Changelog for 2018
ClickHouse Release 18.16
ClickHouse Release 18.16.1, 2018-12-21
Bug Fixes:
Improvements:
Build Improvements:
ClickHouse Release 18.16.0, 2018-12-14
New Features:
Bug Fixes:
Improvements:
Build Improvements:
Backward Incompatible Changes:
ClickHouse Release 18.14
ClickHouse Release 18.14.19, 2018-12-19
Bug Fixes:
Build Improvements:
ClickHouse Release 18.14.18, 2018-12-04
Bug Fixes:
Build Changes:
ClickHouse Release 18.14.17, 2018-11-30
Bug Fixes:
ClickHouse Release 18.14.15, 2018-11-21
Bug Fixes:
ClickHouse Release 18.14.14, 2018-11-20
Bug Fixes:
Build Changes:
ClickHouse Release 18.14.13, 2018-11-08
Bug Fixes:
Performance Improvements:
Build Improvements:
ClickHouse Release 18.14.12, 2018-11-02
Bug Fixes:
ClickHouse Release 18.14.11, 2018-10-29
Bug Fixes:
ClickHouse Release 18.14.10, 2018-10-23
ClickHouse Release 18.14.9, 2018-10-16
New Features:
Experimental Features:
Improvements:
Bug Fixes:
Backward Incompatible Changes:
ClickHouse Release 18.12
ClickHouse Release 18.12.17, 2018-09-16
New Features:
Bug Fixes:
Backward Incompatible Changes:
ClickHouse Release 18.12.14, 2018-09-13
New Features:
Improvements
Bug Fixes:
ClickHouse Release 18.12.13, 2018-09-10
New Features:
Experimental Features:
Improvements:
Bug Fixes:
Security Fix:
Backward Incompatible Changes:
Build Changes:
ClickHouse Release 18.10
ClickHouse Release 18.10.3, 2018-08-13
New Features:
Improvements:
Bug Fixes:
Backward Incompatible Changes
Build Changes:
ClickHouse Release 18.6
ClickHouse Release 18.6.0, 2018-08-02
New Features:
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ClickHouse Release 18.5
ClickHouse Release 18.5.1, 2018-07-31
New Features:
Improvements:
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ClickHouse Release 18.4
ClickHouse Release 18.4.0, 2018-07-28
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Backward Incompatible Changes:
ClickHouse Release 18.1
ClickHouse Release 18.1.0, 2018-07-23
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Backward Incompatible Changes:
ClickHouse Release 1.1
ClickHouse Release 1.1.54394, 2018-07-12
New Features:
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ClickHouse Release 1.1.54390, 2018-07-06
New Features:
Improvements:
Bug Fixes:
Security Fix:
ClickHouse Release 1.1.54388, 2018-06-28
New Features:
Experimental Features:
Bug Fixes:
Improvements:
Build Changes:
Backward Incompatible Changes:
ClickHouse Release 1.1.54385, 2018-06-01
Bug Fixes:
ClickHouse Release 1.1.54383, 2018-05-22
Bug Fixes:
ClickHouse Release 1.1.54381, 2018-05-14
Bug Fixes:
ClickHouse Release 1.1.54380, 2018-04-21
New Features:
Improvements:
Bug Fixes:
Backward Incompatible Changes:
ClickHouse Release 1.1.54378, 2018-04-16
New Features:
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ClickHouse Release 1.1.54370, 2018-03-16
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ClickHouse Release 1.1.54362, 2018-03-11
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Backward Incompatible Changes:
ClickHouse Release 1.1.54343, 2018-02-05
ClickHouse Release 1.1.54342, 2018-01-22
ClickHouse Release 1.1.54337, 2018-01-18
New Features:
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Build Improvements:
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Please Note When Upgrading:
Changelog for 2017
ClickHouse Release 1.1.54327, 2017-12-21
ClickHouse Release 1.1.54318, 2017-11-30
ClickHouse Release 1.1.54310, 2017-11-01
New Features:
Backward Incompatible Changes:
Bug Fixes:
Build Improvements:
ClickHouse Release 1.1.54304, 2017-10-19
New Features:
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ClickHouse Release 1.1.54292, 2017-09-20
New Features:
Bug Fixes:
ClickHouse Release 1.1.54289, 2017-09-13
New Features:
Bug Fixes:
Improved Workflow for Developing and Assembling ClickHouse:
Please Note When Upgrading:
ClickHouse Release 1.1.54284, 2017-08-29
ClickHouse Release 1.1.54282, 2017-08-23
ClickHouse Release 1.1.54276, 2017-08-16
New Features:
Main Changes:
Backward Incompatible Changes:
Complete List of Changes:
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Improved Workflow for Developing and Assembling ClickHouse:
ClickHouse Release 1.1.54245, 2017-07-04
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Minor Changes:
Bug Fixes:
Roadmap
Fixed in ClickHouse <IP_ADDRESS>, 2021-04-12
CVE-2021-25263
Fixed in ClickHouse Release <IP_ADDRESS>, 2019-09-10
CVE-2019-15024
CVE-2019-16535
CVE-2019-16536
Fixed in ClickHouse Release <IP_ADDRESS>, 2019-09-20
CVE-2019-18657
Fixed in ClickHouse Release 18.12.13, 2018-09-10
CVE-2018-14672
Fixed in ClickHouse Release 18.10.3, 2018-08-13
CVE-2018-14671
Fixed in ClickHouse Release 1.1.54388, 2018-06-28
CVE-2018-14668
Fixed in ClickHouse Release 1.1.54390, 2018-07-06
CVE-2018-14669
Fixed in ClickHouse Release 1.1.54131, 2017-01-10
CVE-2018-14670
What’s New in ClickHouse?


Demo Express
Back To Demo
Basic Stuff
Message Queues
FILE UPLOAD
REFRESH TOKEN
Demo Vue SPA Without Bundler


Part-of-Speech Tagging / Normalization of the text in english language Description
Normalization of text is called to bring all the words of the text to the dictionary form: in the nominative case, a single number (if any) or the infinitive for verbs.
Normalization is necessary, for example, to quickly find words in dictionaries, syntactic and semantic analysis of the text.
This procedure is especially important for language grammatical groups, such as russian or finnish, whose rich morphology (strong inflection in the investigation of the grammatical variation).
Normalization is a disambiguation with and without it.
(Homonymy - Match words, the semantic values which does not involve).
Disambiguation means that a particular algorithm selected one word from the set of proposed morfoslovarem.
Disambiguation - it time-consuming and costly in time and resources.
Therefore, it is not often used in text processing systems, and cost "Stemming" - bringing the words to a normal form by the end of it.
In this case, selecting from a plurality of normal form is random.
Methods disambiguation different. The basis of most of them is the morphological and chastirechny analysis of each word, followed by the imposition of the rules of coordination and management.
A special feature of this module is that it involves the entire sequence of linguistic processing of text:
- - the text is divided into proposals;
- - defined parts of speech of words of text (called PoS-tagging - Part-of-Speech tagging);
- - morphological characteristics are all words;
- - removed homonymy;
The processing speed of this module is about 350 KB/sec.


| Uraplast W 8 General Information
-
| Molecular Weight: |
900 (approx) |
| Chemical Category: |
Polymeric plasticizers |
Usage and Performance Characteristics
-
| Manufacturer: |
DSM Resins bv |
| Outstanding Properties: |
Oil & heat resistance, low temperature flexibility |
| Used for Polymeric Materials: |
PVC |
| Used for Products: |
Artificial leather, construction & electrical foils & tapes |
| Extraction, heptane 24 h at 23°C, %: |
1.5 (40 phr); 2 (60 phr); 4.5 (80 phr) |
| Extraction, peanut oil 24 h at 70°C, %: |
2 (40 phr); 3.5 (60 phr); 5 (80 phr) |
| Low-temperature Flexibility, °C: |
2 (40 phr); -15 (60 phr); -26 (80 phr) |
| Migration to PE 10 days at 70°C, %: |
0.9 (40 phr); 1 (60 phr); 1.2 (80 phr) |
| Migration to PS 10 days at 70°C, %: |
0.7 (40 phr); 1.8 (60 phr); 3 (80 phr) |
| Volatility, wt. %: |
0.36 (24 h at 100°C, 40 phr); 0.42 (24 h at 100°C, 60 phr); 0.5 (24 h at 100°C, 80 phr) |
Physical Properties
-
| Aggregate State at 25°C: |
Liquid |
| Tensile Strength, MPa: |
30 (40 phr); 27 (50 phr); 23 (60 phr); 20 (70 phr); 18 (80 phr) |
| 100% Modulus, MPa: |
16 (40 phr); 13 (50 phr); 10 (60 phr); 7 (70 phr) |
| Density, kg/m3: |
>1,035 (25°C) |
| Ultimate Elongation, %: |
320 (40 phr); 350 (50 phr); 380 (60 phr); 400 (70 phr) |
Chemical Properties
-
| Acid Number, mg KOH/g: |
<1 |
Optical Properties
-
| Refractive Index: |
1.502 (n25D) |
Plasticizers Database (2nd Electronic Edition) Copyright © 2004 by ChemTec Publishing |


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Blockchain Capstone
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TOUT LES MATINS DU MONDE [Spoilers] A film review by<EMAIL_ADDRESS>Copyright 1993<EMAIL_ADDRESS>Comments on TOUS LES MATINS DU MONDE, SPOILERS!!!!
When I think of the predicament of French cinema, I envision a delicate Columbine doll labeled ART being torn apart by a mastiff labeled THOUGHT AND REASON. The tendency towards philosophical abstraction has been the curse of French film since Renoir, culminating in the soporific headiness of such master anaesthetists as Bresson and Rohmer. My own list of the 12 greatest films contains a single French entry, Clement's FORBIDDEN GAMES (1951). That film spoke movingly of the horrifying effect of war on children; no philosophical meditations crippled its direct and harrowing message.
But in French film, such achievements are rare, and seem almost to have to apologize for their presence. There was a time when I thought French film might be rescued from its philosophical diaspora. I welcomed Godard's BREATHLESS (1960), and even WEEKEND (1968), but that director began to descend into bombast and politically trendy rant. Once in a while a filmmaker such as Cocteau in LES ENFANTS TERRIBLE (1950) would approach a robust subject, then scurry away in cant and confusion, leaving an unwatchable film. The promise of LA FEMME NIKITA and DELICATESSEN remains to be fulfilled.
It is remarkable that French cineasts admire from afar a completely different approach to filmmaking, the American film noir genre, with its frenetic sense of doom and its headlong momentum.  None of these films is free from flaws, but each grabs the viewer by the scruff of the neck neck at the beginning and at the end propels him/her out of the theater wondering how 1 1/2 hours could have passed so quickly. The momentum films in this genre are capable of building is truly marvelous. The noir spirit of these films is the antithesis of what the French filmmakers themselves usually achieve. French filmmakers are like the acnaed high school computer whiz who fantasizes about the cheerleader he can never have.
The recent film, TOUS LES MATINS DU MONDE (All The Mornings of the World) is, alas, in the reflective tradition. The film details the relationship between the baroque composers Marin Marais (1656-1728) and M. de Sainte Colombe, played by Gerard Depardieu and Jean-Pierre Marielle, respectively. Marais is best known, perhaps, for his unearthly "Les Sonnerie de Sainte Genevieve du Mont-de-Paris" which is often played on the classical music stations. I am uncertain about the historicity of Marielle's character. He is certainly obscure, not even being listed in my Slonimsky. However, some recordings of his music have begun to emerge. In the film Marais is depicted as his protege, but in reality Marais studied the viola da gamba with Hotterman, and composition with Lully. Their relationship is the usual protege relationship enshrined in filmdom: melodramatic, filled with sullen abrasiveness, temperament, posturing, and in this case with a seduced, pining and ultimately suicidal daughter.
The film is langorous and atmospheric, and the interplay of the haunting baroque music with the pastoral scenery is effective. The actors handle their duties adroitly, particularly Marielle, and that reliable fireplug of an actor, Depardieu. French actors are, I think, the best film actors. Everything comes from the face, and everything is nuance. French actors and directors both have obviously studied the great American film actors of the past. It is interesting that Stephen Frears, the director of LIASONS DANGEREUSE, cast that film with American, rather than French, actors because "American actors are better with their faces." I don't think so. More than once, during the films JEAN DE LA FLORETTE and MANON OF THE SPRING I burst into spontaneous applause at the intense subtlety of the performances, particularly those of Daniel Auteuil and Yves Montand. When I saw LA FEMME NIKITA, there was a unified intake of breath from the audience during Jeanne Moreau's bravura turn as the aging crone. I could name many other equally thrilling examples. Marielle in the present film is so uncanny that one could easily watch him read a telephone book, or Descartes' "Discourse on Method," which is an asset, because in this movie that's about what the viewer gets.
Yes, unfortunately that age-old succubus of French film, THE IDEA, is at work. Seeing the device called "faction"--- historical figures in an imagined narrative---in the hands of a French director is ominous, like a toddler playing with a handgun. It means the characters can be anything, in particular, puppets, from whose mouths can me made to issue maxims, alternatively opaque and sophomoric. The motivations and consistency of character in the movie are really non-existent; Marais' dialog could be given to Sainte Colombe or vice versa with no discernible effect. The characters are pegs on which to hang a series of ruminations about art and life. The character of the young Marais, played by Depardieu's real life son, makes no sense whatsoever. He weeps when upbraided by Sainte Colombe and denounces him as a cruel man, yet, with no hesitation, walks out on his pregnant lover. "Our bodies are no longer right for each other."
There is no historical evidence that Marais liked to dally destructively. In fact, he married at the age of 20 and had 19 devoted children. More faction, I suppose.
The film culminates in a ultra-slow-motion Socratic dialog between St. Colombe and his errant pupil Marais on the nature of art and life.
"What is music for?" St. Colombe asks, pensively. The scene is filmed in near darkness, the actor's faces fill the screen, an encyclopedia of facial expressions is exhibited before each word of dialog emerges.
To this question, Marais offers a languid series of abstruse replies, each of which is countered by a severe "NO!" from St. Colombe. Finally, the secret is revealed.
"Music is for before we are born, before we breathe, before we see the light."
Watching this philosophical paint dry became excruciating, unendurable. I estimated my distance from the exit doors. I found myself conjuring up new muffin recipes. I found myself thinking of imaginative ways to re-wire my house and reappraising the promises of that morning's junk mail. I renewed my promise never to shout "FRENCH CINEMA!" in a crowded fire station.
.
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One night in the late summer, my older sister and her friend decided that since I live legally clean through necessity but have a fondness for altered states of consciousness, she would both fund and monitor a Salvia Divinorum trip for me. A kind gift from a kind family member. It's that kind of family.
A little background, I'd tried Salvia Divinorum before, six years prior, but all it gave me then was an uncomfortable vibrating sensation and a feeling that the silk shirt that I was sweating through had somehow turned to burlap. I was willing to try it again, admitting to myself that the last time I had partaken of this substance, it was a low dosage and I wasn't really willing to give anything back to it.
Back to the story at hand. We went to her friend's small studio apartment and after sorting through a rather impressive music collection, we decided on some Massive Attack for 'traveling' music. Mellow enough, but not without well defined rhythm, which is important to me, as I've used music as a ground in the past. A way to find my way home. Just in case. He offered me his bed or a reclining chair, but the floor is really more of my thing. Dirty apartment carpet is good enough. One can't fall off the carpet.
I leaned against a bookshelf, crowded with Robert Anton Wilson books and old pulp science fiction novels and tried to prepare myself for the experience. All I had to go on was a dim memory of one interesting though mildly unpleasant prior experience and the promise that this was of much higher quality and potency than whatever I'd had before and that I'd only scratched the surface before. The only foreign chemicals in my system at that point were caffeine and nicotine.
First hit botched slightly: The smoke tasted like acidic mud. Swampy. Harsh. I tipped the pipe back too far and got some of the water in my mouth. This also tasted like mud. Swampy. I spit the water into my hand and wiped it into my jeans. I held the smoke for maybe fifteen seconds, give or take a couple. The smoke was very harsh, but I managed not to cough.
First hit, Take Two: More confident, now, I tried again. This time, it was a VERY large hit. I filled my lungs as full as I could comfortably fill them and held the smoke in as long as I could. Twenty or thirty seconds. I exhaled again slowly, feeling a familar sensation of vibration. My sister asked me if I wanted to hit the pipe again. I told her sure, but to wait until I was done rolling forward, as that's exactly the sensation I was experiencing. That, and the feeling that I was being pressed downward by a blanket of incredibly strong static electrical current.
I sat, letting the sensation wash over me, but then I found the position I was in to be uncomfortable, so after a bit of experimenting, I persuaded my limbs to direct me to a more comfortable position, lying on my stomach in the middle of the floor. That's the last I saw of that apartment for a little while.
My memory jumps to a very specific image: I saw a vaguely circular pattern, a sliver of silvery white on the right and the rest more of a maroon color, seeming to spin counter-clockwise, vertically, facing me. Maybe ten feet away? Maybe ten miles? Ten million years? It seemed to be resting(?) in a pool of water. I got the impression of a rich swamp, minus the vegetation. My guess is that most of that impression was due to the swampy taste in my mouth and the large wet spot on the outside of my left knee, where I had wiped the water.
This image just WAS. It seemed to rest in one place, but it was spinning too fast to accurately describe its state as 'resting'. It was the entirety of reality and I was just one observer. The only observer. Ever. It seemed to be very powerful and VERY foreign. Alien, but not in any outer-space Hollywood blockbuster kind of way. Just the most foreign thing I could possibly perceive at that moment. I felt that it was in the far past and the only thing that had ever existed wherever/whenever it was. It was unique, ancient, aware. I was all alone with it.
I became aware of its voice. It seemed to be communicating through what I assume was the bassline of one of the Massive Attack songs. I'll have to listen to that album and see if I can find that particular bass line. It seemed to be using it as its voice. It seemed to be telling me something very important, and I was trying to understand. Like Moses climbing to the mountain top only to find out that God spoke Spanish. I needed to understand it. The need was urgent.
About that time, my sister bless her soul, got the impression that I was in some kind of distress. She did something to interrupt my 'communication'. I distinctly remember being both very annoyed at her for bothering me and very glad that she was there, because she is my sister and I love her. I heard her laugh and I was laughing, too. I was once again aware of being in the room.
I made myself sit up, after a bit and heard her friend tell her that it was her turn. I was trying to communicate my experience to her, but I was having some trouble making my mouth work, like I had to teach myself to talk over again so I could make words. I remember telling her that now she could be the only servant/student/witness of, and tried to describe it by making a counter-clockwise motion with my left hand and fore-arm. It was all I could do.
This of course elicited more laughter from my sister and her friend. I became more aware of the room and my surroundings. I waited for her to take her hit and since I seemed to be lucid and in control of myself, her friend also had some. There was still some left in the bowl after her friend had had his share, so I decided to try to regain the state I had attained and lost. It didn't work. I managed to find a place to put the pipe where it was out of the way and reclined in the chair. Just the physical sensation. No more of the frontal-lobe massage that I was looking for.
Once I was able to make words, I was trying to tell them about it, but my sister didn't get past the physical sensation and wouldn't allow the Salvia Divinorum to tell her what it needed to. She said she just felt hot and itchy and it was hard for her to move.
Overall, I'd say that the smoked herb stimulated the part of my frontal lobe that's tied to spirituality and thumped it very hard. I could describe the experience as looking at God's baby-picture and not feel like I was exagerating much. I experienced a distorted perception of time and space, in the company of or perhaps aided by extremely impaired motor skills (I couldn't TALK for fuck's sake!) and a dramaticly reduced sense of balance.
The sweating and itching, I'm not terribly certain what causes this, but my sister's friend describes it as being similar to the effect of a super-dose of Niacin. I believe that's what he said. He described it as dilating the capillaries, causing a lot of body heat to come to the surface. That's all I know and can relate at the moment. I hope it's informative, useful, or at least entertaining to someone.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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North Korea calls Biden 'rabid dog' that 'must be beaten to death'
SEOUL: North Korea launched a visceral diatribe against US Democratic presidential candidate Joe Biden, calling the former vice-president a "rabid dog" - while also borrowing the terminology of Donald Trump.
Pyongyang is renowned for its vitriol, but the verbal deluge was unusually ferocious even by its own standards.
Biden "had the temerity to dare slander the dignity of the supreme leadership of the DPRK", the North's official KCNA news agency said late Thursday, referring to the country by its official name.
"Rabid dogs like Biden can hurt lots of people if they are allowed to run about," it went on. "They must be beaten to death with a stick.
"Doing so will be beneficial for the US also," it added.
READ: Trump, Kim mind their body language with a handshake of equals
It was not immediately clear what had provoked Pyongyang's ire, but Biden's campaign on Friday seemed to relish the attack.
"It seems that murderous dictator Kim Jong Un doesn't like me," Biden said in a statement. "Add him to the list of autocrats who don't want me to be president - right next to Vladimir Putin. I wear their insults as a badge of honor."
Trump said that "he and Kim 'fell in love' - well, there will be no love letters in a Biden Administration", the former vice president said.
Biden, who vowed not to "embrace dictators", said that Trump is "emboldening" the North Korean leader.
Kim "would love to see Trump re-elected, as would the rest of America's adversaries. That's just one more reason it's so important we beat him next November", Biden said.
KIM A 'TYRANT'
The Biden campaign earlier released an ad condemning Trump's foreign policy, saying that "dictators and tyrants are praised, our allies pushed aside".
The voiceover says the word "tyrants" at the exact moment a picture appears of Trump and Kim shaking hands at their Singapore summit last year.
KCNA appeared to cite one of Trump's favoured insults for the candidate - "Sleepy Joe" - when it said Americans called him "Biden not awakened from a sleep".
Biden had shown "a sign of the final stage of dementia", KCNA added. "It seems time has come for him to depart his life."
KCNA misspelled the candidate's name as "Baiden" throughout, seemingly reflecting the spelling used in the Korean alphabet.
READ: North Korea slams Joe Biden for criticising leader Kim Jong Un
It is not the first time the North has condemned Biden. In May it called him an "imbecile" and a "fool of low IQ" days after he called Kim a "dictator" and "tyrant."
The North Korean rhetoric underscores its "impatience" with any criticism of Kim, said Cheong Seong-Chang, a senior researcher at the private Sejong Institute.
"Pyongyang has always loathed hearing its leadership labelled as tyrant or dictator by the outside world," he said.
The invective against Biden was "pretty high on the scale", North Korean propaganda specialist Mason Richey of Hankuk University of Foreign Studies told AFP, highlighting the multiple repetitions of the "beating the dog" trope.
Trump himself has also been the target of Pyongyang's anger at times.
In 2017 the two leaders traded personal insults and threats of war before the diplomatic rapprochement that has seen them meet three times and Trump repeatedly proclaim their personal friendship, although nuclear negotiations remain deadlocked.
As tensions mounted, Kim called Trump a "mentally deranged US dotard" whom he would "tame with fire", while KCNA also branded him a "rabid dog".
KCNA used the same Korean word previously translated as "dotard" in its article Thursday, although the epithet did not appear in the official English version.


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California Incident Map¶
This service provides tools for the user to inspect location of incidents on a California Map. It is recommended to use a small date range for full functionality. This is a data visualization tool and hence depends only on the data set and not rely on any backend functionality.
How to use¶
The first is the filter, where you selection the time of interest to see california wide fire incidents. You can zoom in on the map, and use provided tools like lasso to select a certain are and then see the incidents in a dataframe.
For example, if one selects the range of inspection as the whole month of January 2021 and decides to inspect the LA and Santa Barbara area, we see on the map the fire incidents.
Dashboard elements and the functions used¶
There are two dashboard elements in this tool- 1. Wildfires Incident Map 2. Dataframe with additional information.
1. Wildfires Incident Map¶
The first thing you see on this page is the map of california indicating the fires that are happening. Note- The scatter plot seen on the map is representative of relative intensity of the fires.
1.1 Update_cali_map¶
When you hover over a particular fire, you can also visually see some statistics about the fire such as acres burned , latitude and longitude. This is done with the help of this function. Below is the function signature.
2. Dataframe with additional information¶
Continuing our example, when we select LA - Santa Barbara area for the month of January,2021 the dataframe observed is-
2.1 Display_data¶
If we use the Box Select or the Lasso tool to select a particular area on the california map, then we get more information such as Incident Name , Incident administrative unit , Incident location for all the fires in the selected area.


{{_("Dear")}} {{ fullname }},
{{_("Please find the list of Support Tickets that are still open and can not be escalated further")}}
{{_("Thank you")}}, {{_("Team HelpDesk")}}


function SetSize(NewWidth, NewHeight: Integer): Boolean; override;
procedure SetSize(Source: TPersistent); // implemented in TCustomMap
Call SetSize to set new dimensions of the bytemap. If one of the arguments is zero, the bytemap is considered empty and its Bits property is set to nil.
Calling SetSize works faster than changing both Width and Height properties.
If you use another bitmap, byte map or control as an argument, the byte map will be sized to corresponding dimensions.


{% extends 'pages/baseStudents.html' %} {% load static %} {% block content %}
Note: Please fill the above options correctly, this will allow your Tasks to be appear from respective instructors!


Ladysmith Black Mambazo
The man behind the musical success called Ladysmith Black Mambazo
Bhekizizwe Joseph Siphatimandla Mxoveni Mshengu Bigboy Shabalala, was a South African singer and musician from Ladysmith who was the founder and musical director of the choral group Ladysmith Black Mambazo.
1958: he searched for work in the nearby city of Durban whereby he was spotted by a well-known group, the Durban Choir, after he delighted audiences with his smooth guitar playing and soprano voice. When he joined the choir, he attempted to teach them some of his new compositions, namely his first song "Nomathemba" (which was made into a play in 1995). They refused, and so he left them after only two years.
1958: Shabalala discovered an isicathamiya group, The Highlanders, led by his hero Galiyane Hlatshwayo. Hlatshwayo was the man who encouraged Shabalala to use his voice powerfully
1959: Shabalala formed his own group called Ezimnyama "The Black Ones".
1960: He had a series of dreams in his sleep in December 1960 was a major turning point in the formation of the group; when he saw how well his group did in the once-weekly isicathamiya competitions, he renamed them Ladysmith Black Mambazo, "Mambazo" meaning axe, referring to how the group chopped down the other choirs by winning almost every time.
1972: After local radio airplay (on the S.A.B.C. station Radio Zulu), Shabalala accepted a recording contract that was offered by Gallo Music producer West Nkosi. The group sold over 40,000 copies of their first album and continued to do so through other recordings.
1976: He became a Christian, and the songs in the Mambazo repertoire were shuffled to one side to include generalized Christian, Methodist, and Zionist hymns sung in the Zulu language.
1986: Paul Simon travelled to South Africa to collaborate with South African artists for his upcoming Graceland album. Simon collaborated with Shabalala and the group, and co-composed the now-famous song, "Homeless". The group's popularity spread all over the world, and since then they have sold records popular enough to earn platinum disc certification. In 1987, the group won their first solo Grammy Award for Shaka Zulu. Since then, they have won one more and have been nominated over ten times. Following the worldwide success of Graceland, Shabalala began composing more songs in English (prior to this they had only recorded two in English and one in German).
2008: Shabalala announced, in January 2008, that his youngest son Thamsanqa would take over as leader of Ladysmith Black Mambazo when the time comes for him to retire from international touring.
2020: 11 February 2020, Shabalala died in Pretoria at the age of 78


I have personally worked on some projects and the links are provided below
please do feel free to visit the links and have a look at the amaizing work done.
The projects that i have made work properly with no issues
The link below will lead you to my github account where you will see my project
I personally have an experience of 160hours of cooding since is started to learn coding
The following are the reasons why i decided to learn code
I generally like playing out door games since i am multi talented i can say all games will do with me
Writing code has become part of me these days so its also my interes


I have been troubleshooting hardware and software for over 15 years
With knowledge of ColdFusion, HTML, CSS, JavaScript, T-SQL
& of the supporting infrastructure Windows and MS SQL
Interested in getting started?
Let Me KnowReady to start your next project with me? Let's get started
123.456.6789


Stockholm hospitals to cut hundreds of jobs amid growing budget deficit
by The LocalTwo Stockholm hospitals on Monday announced plans to cut hundreds of jobs, just a few weeks after another major hospital warned it was laying off 600 medical staff.
Danderyd Hospital warned in a statement that it would be laying off around 100 staff as part of a drive to plug an estimated budget deficit of 156 million kronor ($16.22 million) this year.
The hospital plans to eventually cut around 250 jobs in total.
"We have worked together within the hospital to find savings. It's substantial work and we are not yet finished," said hospital CEO Yvonne Haglund Åkerlind in a statement.
Earlier on Monday, Södersjukhuset announced plans to cut 100 jobs at the hospital in Stockholm, including 50 nursing assistants, 25 doctors and 25 administrative jobs.
The hospital warned that a 130 million kronor budget deficit in 2019 could grow to 300 million next year without the job cuts, which come amid a series of other measures.
Both hospitals have already put in place decisions not to hire new staff or temporary staff via agencies, and to implement stricter control of purchases to ensure that administrative costs are kept at a minimum.
The news comes just weeks after Sweden's Karolinska Hospital announced plans to lay off 600 medical staff, which in turn followed a decision to slash 550 administrative jobs in May.
FOR MEMBERS: Everything you need to know if you lose your job in Sweden


DELIVERING THE FUTURE OF BIG DATA INTEGRATION AND ANALYTICS Pentaho, a Hitachi Group company, is a leading data integration and business analytics company with an enterprise-class, open source-based platform for diverse big data deployments. Our mission is to help organizations across industries harness the value from all their data, including big data and Internet of Things (IoT), enabling them to find new revenue streams, operate more efficiently, deliver outstanding service and minimize risk. The Sales Engineering Team is dedicated to support prospects in their evaluation of Pentaho.
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Enter a domain name and check if it is available for registration.
To register the domain, please enter your contact and payment details below.
The domain name example.com is now registered on your behalf.


Above in the drop-down menus are the various lab exercies assigned for this course, as well as links to the projects that were portable enough to link here.
For Project 1, we wrote our own server to manage and serve a calendar web application. Since we wrote it from scratch, it wasn't feasible to adapt it to run on the KU servers.
For Project 2, we took over another team's project 1 and wrote additional features for it. We were locked in to the platform and style they chose, hence the drastic difference in presentation and implementation. See 'Adopt-a-project' above.


Google Analytics¶
Customizing Federal Google Analytics¶
Federally sponsored websites are required to have Google Analytics installed.
This version of Google Analytics sends information back to the Office of Management and Budget (OMB). It does not send information back to your agency, site, or node administrator.
CoG comes with pre-installed Google Analytics with options to set various variables for any particular agency.
The Default¶
By default, the CoG instance will load a file /templates/cog/common/google_analytics.html that is empty.
Overriding the Default¶
Sites that want to insert their own Google Analytics must place a customized version of the default file into
$COG_CONFIG_DIR/mytemplates/cog/common/google_analytics.html


Write the type of org you are here -- choose from: Non-Profit, Not-Just-For-Profit, For-Profit
Write your mission statement here.
Product One Name - Describe product 1 in a few words
Product Two Name - Describe product 2 in a few words
In this project we learned to work collaboratively, incrementally
and how to
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Becoming a member is easy!
Print out an application form and fill in your details. Then either send it in, or bring it along to the next club meeting.
Not sure about joining the club? Come along to a meeting, guests are welcome.


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Lita Beach
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Contact Lita:
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Sorting Out Sorting
Computers 3 Tompsett
Author: Owen Lynch, graphs credit to CanvasJS.com
From this graph we can clearly see that as long as you don't pick insertion sort, selection sort, or especially bubble sort you'll be fine. Obviously sorting is not as simple as this, so I have also included other graphs.
The weird thing here is that counting sort actually takes a shorter average time to run on the 100,000 element arrays than it did on the 75,000 element arrays. I honestly have no idea why. The reason these graphs don't look like logarithmic graphs is because the x axis is strange.
It's unfortunate that counting sort dominates the scale of this graph. Interesting highlights nonetheless include a very low average for insertion sort. Clearly for small arrays, insertion sort is the way to go. One surprise here was heap sort's win over quicksort; it seems that its lack of heavy recursion was a boon.
Again, insertion sort has the lead, which surprised me; I though we'd see one of the \( \mathcal{O}(n\log n) \) sorts come up ahead here. Otherwise, similar to the length 10, though bucket sort only doubled, growing far more slowly than anything else. Counting sort as well stayed basically constant.
Insertion sort still is winning here, though quick sort is catching up.
Finally, insertion sort gives up the lead, and quicksort takes it for a while. Heapsort continues to do remarkably well, given its complexity, and bucket sort has caught up and started to perform better than merge sort, even.
Same trends as 500.
Bucket sort takes the lead, barely edging out quick sort! Counting sort is also back in the game.
Quicksort remains quite good, but it just can't compete with the \( \mathcal{O}(n) \) bucket sort.
Even with the O(nlogn) runtime, quicksort remains very competetive with the two \( \mathcal{O}(n) \) sorts.  I'm sure many of you are just as surprised as I am, it's been a long race, and I'm sure many of you who bet good money on quicksort have been sorely dissapointed.
In the final leg, counting sort goes in almost half the time of any other, with bucket sort and quick sort runners up. I must say, it's been an exciting day.
Big-O's
- Bubble Sort: \( \mathcal{O}(n^2) \)
- Merge Sort: \( \mathcal{O}(n\log n) \)
- Quick Sort: \( \mathcal{O}(n\log n) \)
- Insertion Sort: \( \mathcal{O}(n^2) \)
- Selection Sort: \( \mathcal{O}(n^2) \)
- Heap Sort: \( \mathcal{O}(n\log n) \)
- Counting Sort: \( \mathcal{O}(n) \)
- Bucket Sort: \( \mathcal{O}(n) \)