This capability comes at a cost: additional disk and memory overheads and higher insertion costs when adding new rows to the table and entries to the index (and also sometimes rebalancing of the B-Tree). Because the hash column is used as the primary key column. Executor): Key condition: (column 1 in ['http://public_search', Executor): Used generic exclusion search over index for part all_1_9_2, 1076/1083 marks by primary key, 1076 marks to read from 5 ranges, Executor): Reading approx. In order to have consistency in the guides diagrams and in order to maximise compression ratio we defined a separate sorting key that includes all of our table's columns (if in a column similar data is placed close to each other, for example via sorting, then that data will be compressed better). Specifically for the example table: UserID index marks: we switch the order of the key columns (compared to our, the implicitly created table is listed by the, it is also possible to first explicitly create the backing table for a materialized view and then the view can target that table via the, if new rows are inserted into the source table hits_UserID_URL, then that rows are automatically also inserted into the implicitly created table, Effectively the implicitly created table has the same row order and primary index as the, if new rows are inserted into the source table hits_UserID_URL, then that rows are automatically also inserted into the hidden table, a query is always (syntactically) targeting the source table hits_UserID_URL, but if the row order and primary index of the hidden table allows a more effective query execution, then that hidden table will be used instead, please note that projections do not make queries that use ORDER BY more efficient, even if the ORDER BY matches the projection's ORDER BY statement (see, Effectively the implicitly created hidden table has the same row order and primary index as the, the efficiency of the filtering on secondary key columns in queries, and. Its corresponding granule 176 can therefore possibly contain rows with a UserID column value of 749.927.693. Provide additional logic when data parts merging in the CollapsingMergeTree and SummingMergeTree engines. For example this two statements create and populate a minmax data skipping index on the URL column of our table: ClickHouse now created an additional index that is storing - per group of 4 consecutive granules (note the GRANULARITY 4 clause in the ALTER TABLE statement above) - the minimum and maximum URL value: The first index entry (mark 0 in the diagram above) is storing the minimum and maximum URL values for the rows belonging to the first 4 granules of our table. // Base contains common columns for all tables. An intuitive solution for that might be to use a UUID column with a unique value per row and for fast retrieval of rows to use that column as a primary key column. https://clickhouse.tech/docs/en/engines/table_engines/mergetree_family/mergetree/. Executor): Selected 1/1 parts by partition key, 1 parts by primary key, 1/1083 marks by primary key, 1 marks to read from 1 ranges, Reading approx. The primary key needs to be a prefix of the sorting key if both are specified. A long primary key will negatively affect the insert performance and memory consumption, but extra columns in the primary key do not affect ClickHouse performance during SELECT queries. We discuss a scenario when a query is explicitly not filtering on the first key colum, but on a secondary key column. Spellcaster Dragons Casting with legendary actions? In contrast to the diagram above, the diagram below sketches the on-disk order of rows for a primary key where the key columns are ordered by cardinality in descending order: Now the table's rows are first ordered by their ch value, and rows that have the same ch value are ordered by their cl value. Because data that differs only in small changes is getting the same fingerprint value, similar data is now stored on disk close to each other in the content column. This is one of the key reasons behind ClickHouse's astonishingly high insert performance on large batches. The primary index that is based on the primary key is completely loaded into the main memory. ClickHouseMySQLRDS MySQLMySQLClickHouseINSERTSELECTClick. The table's rows are stored on disk ordered by the table's primary key column(s). As the primary key defines the lexicographical order of the rows on disk, a table can only have one primary key. For both the efficient filtering on secondary key columns in queries and the compression ratio of a table's column data files it is beneficial to order the columns in a primary key by their cardinality in ascending order. It just defines sort order of data to process range queries in optimal way. Sparse indexing is possible because ClickHouse is storing the rows for a part on disk ordered by the primary key column(s). The primary index file needs to fit into the main memory. In order to illustrate that, we give some details about how the generic exclusion search works. Sparse indexing is possible because ClickHouse is storing the rows for a part on disk ordered by the primary key column (s). . Update/Delete Data Considerations: Distributed table don't support the update/delete statements, if you want to use the update/delete statements, please be sure to write records to local table or set use-local to true. ClickHouse. In parallel, ClickHouse is doing the same for granule 176 for the URL.bin data file. 8028160 rows with 10 streams, 0 rows in set. The following diagram shows the three mark files UserID.mrk, URL.mrk, and EventTime.mrk that store the physical locations of the granules for the tables UserID, URL, and EventTime columns. The following diagram illustrates a part of the primary index file for our table. Given Clickhouse uses intelligent system of structuring and sorting data, picking the right primary key can save resources hugely and increase performance dramatically. Processed 8.87 million rows, 838.84 MB (3.06 million rows/s., 289.46 MB/s. The uncompressed data size is 8.87 million events and about 700 MB. ClickHouse chooses set of mark ranges that could contain target data. The last granule (granule 1082) "contains" less than 8192 rows. It just defines sort order of data to process range queries in optimal way. Such an index allows the fast location of specific rows, resulting in high efficiency for lookup queries and point updates. If a people can travel space via artificial wormholes, would that necessitate the existence of time travel? The located compressed file block is uncompressed into the main memory on read. Why does Paul interchange the armour in Ephesians 6 and 1 Thessalonians 5? This can not be excluded because the directly succeeding index mark 1 does not have the same UserID value as the current mark 0. We will use a subset of 8.87 million rows (events) from the sample data set. ", What are the most popular times (e.g. It only works for tables in the MergeTree family (including replicated tables). 'https://datasets.clickhouse.com/hits/tsv/hits_v1.tsv.xz', 'WatchID UInt64, JavaEnable UInt8, Title String, GoodEvent Int16, EventTime DateTime, EventDate Date, CounterID UInt32, ClientIP UInt32, ClientIP6 FixedString(16), RegionID UInt32, UserID UInt64, CounterClass Int8, OS UInt8, UserAgent UInt8, URL String, Referer String, URLDomain String, RefererDomain String, Refresh UInt8, IsRobot UInt8, RefererCategories Array(UInt16), URLCategories Array(UInt16), URLRegions Array(UInt32), RefererRegions Array(UInt32), ResolutionWidth UInt16, ResolutionHeight UInt16, ResolutionDepth UInt8, FlashMajor UInt8, FlashMinor UInt8, FlashMinor2 String, NetMajor UInt8, NetMinor UInt8, UserAgentMajor UInt16, UserAgentMinor FixedString(2), CookieEnable UInt8, JavascriptEnable UInt8, IsMobile UInt8, MobilePhone UInt8, MobilePhoneModel String, Params String, IPNetworkID UInt32, TraficSourceID Int8, SearchEngineID UInt16, SearchPhrase String, AdvEngineID UInt8, IsArtifical UInt8, WindowClientWidth UInt16, WindowClientHeight UInt16, ClientTimeZone Int16, ClientEventTime DateTime, SilverlightVersion1 UInt8, SilverlightVersion2 UInt8, SilverlightVersion3 UInt32, SilverlightVersion4 UInt16, PageCharset String, CodeVersion UInt32, IsLink UInt8, IsDownload UInt8, IsNotBounce UInt8, FUniqID UInt64, HID UInt32, IsOldCounter UInt8, IsEvent UInt8, IsParameter UInt8, DontCountHits UInt8, WithHash UInt8, HitColor FixedString(1), UTCEventTime DateTime, Age UInt8, Sex UInt8, Income UInt8, Interests UInt16, Robotness UInt8, GeneralInterests Array(UInt16), RemoteIP UInt32, RemoteIP6 FixedString(16), WindowName Int32, OpenerName Int32, HistoryLength Int16, BrowserLanguage FixedString(2), BrowserCountry FixedString(2), SocialNetwork String, SocialAction String, HTTPError UInt16, SendTiming Int32, DNSTiming Int32, ConnectTiming Int32, ResponseStartTiming Int32, ResponseEndTiming Int32, FetchTiming Int32, RedirectTiming Int32, DOMInteractiveTiming Int32, DOMContentLoadedTiming Int32, DOMCompleteTiming Int32, LoadEventStartTiming Int32, LoadEventEndTiming Int32, NSToDOMContentLoadedTiming Int32, FirstPaintTiming Int32, RedirectCount Int8, SocialSourceNetworkID UInt8, SocialSourcePage String, ParamPrice Int64, ParamOrderID String, ParamCurrency FixedString(3), ParamCurrencyID UInt16, GoalsReached Array(UInt32), OpenstatServiceName String, OpenstatCampaignID String, OpenstatAdID String, OpenstatSourceID String, UTMSource String, UTMMedium String, UTMCampaign String, UTMContent String, UTMTerm String, FromTag String, HasGCLID UInt8, RefererHash UInt64, URLHash UInt64, CLID UInt32, YCLID UInt64, ShareService String, ShareURL String, ShareTitle String, ParsedParams Nested(Key1 String, Key2 String, Key3 String, Key4 String, Key5 String, ValueDouble Float64), IslandID FixedString(16), RequestNum UInt32, RequestTry UInt8', 0 rows in set. On a self-managed ClickHouse cluster we can use the file table function for inspecting the content of the primary index of our example table. Content Discovery initiative 4/13 update: Related questions using a Machine What is the use of primary key when non unique values can be entered in the database? The engine accepts parameters: the name of a Date type column containing the date, a sampling expression (optional), a tuple that defines the table's primary key, and the index granularity. ClickHouse stores data in LSM-like format (MergeTree Family) 1. The column that is most filtered on should be the first column in your primary key, the second column in the primary key should be the second-most queried column, and so on. In the diagram above, the table's rows (their column values on disk) are first ordered by their cl value, and rows that have the same cl value are ordered by their ch value. If we estimate that we actually lose only a single byte of entropy, the collisions risk is still negligible. 'http://public_search') very likely is between the minimum and maximum value stored by the index for each group of granules resulting in ClickHouse being forced to select the group of granules (because they might contain row(s) matching the query). When the UserID has high cardinality then it is unlikely that the same UserID value is spread over multiple table rows and granules. Because of the similarly high cardinality of UserID and URL, this secondary data skipping index can't help with excluding granules from being selected when our query filtering on URL is executed. ClickHouseClickHouse Processed 8.87 million rows, 15.88 GB (74.99 thousand rows/s., 134.21 MB/s. We are numbering granules starting with 0 in order to be aligned with the ClickHouse internal numbering scheme that is also used for logging messages. However, the three options differ in how transparent that additional table is to the user with respect to the routing of queries and insert statements. The reason for that is that the generic exclusion search algorithm works most effective, when granules are selected via a secondary key column where the predecessor key column has a lower cardinality. If in addition we want to keep the good performance of our sample query that filters for rows with a specific UserID then we need to use multiple primary indexes. The ClickHouse MergeTree Engine Family has been designed and optimized to handle massive data volumes. 2023-04-14 09:00:00 2 . It offers various features such as . Similar to data files, there is one mark file per table column. The stored UserID values in the primary index are sorted in ascending order. (ClickHouse also created a special mark file for to the data skipping index for locating the groups of granules associated with the index marks.). ClickHouse allows inserting multiple rows with identical primary key column values. ClickHouse PRIMARY KEY ORDER BY tuple() PARTITION BY . MergeTreePRIMARY KEYprimary.idx. We have discussed how the primary index is a flat uncompressed array file (primary.idx), containing index marks that are numbered starting at 0. When a query is filtering on both the first key column and on any key column(s) after the first then ClickHouse is running binary search over the first key column's index marks. Note that for most serious tasks, you should use engines from the How to pick an ORDER BY / PRIMARY KEY. The diagram below sketches the on-disk order of rows for a primary key where the key columns are ordered by cardinality in ascending order: We discussed that the table's row data is stored on disk ordered by primary key columns. For ClickHouse secondary data skipping indexes, see the Tutorial. Feel free to skip this if you don't care about the time fields, and embed the ID field directly. For our example query, ClickHouse used the primary index and selected a single granule that can possibly contain rows matching our query. For example, consider index mark 0 for which the URL value is smaller than W3 and for which the URL value of the directly succeeding index mark is also smaller than W3. Pick the order that will cover most of partial primary key usage use cases (e.g. ), Executor): Running binary search on index range for part prj_url_userid (1083 marks), Executor): Choose complete Normal projection prj_url_userid, Executor): projection required columns: URL, UserID, cardinality_URLcardinality_UserIDcardinality_IsRobot, 2.39 million 119.08 thousand 4.00 , , 1 row in set. ClickHouse now uses the selected mark number (176) from the index for a positional array lookup in the UserID.mrk mark file in order to get the two offsets for locating granule 176. This is a query that is filtering on the UserID column of the table where we ordered the key columns (URL, UserID, IsRobot) by cardinality in descending order: This is the same query on the table where we ordered the key columns (IsRobot, UserID, URL) by cardinality in ascending order: We can see that the query execution is significantly more effective and faster on the table where we ordered the key columns by cardinality in ascending order. For index marks with the same UserID, the URL values for the index marks are sorted in ascending order (because the table rows are ordered first by UserID and then by URL). Sometimes primary key works even if only the second column condition presents in select: For tables with wide format and without adaptive index granularity, ClickHouse uses .mrk mark files as visualised above, that contain entries with two 8 byte long addresses per entry. 4ClickHouse . Combination of non-unique foreign keys to create primary key? This compresses to 200 mb when stored in ClickHouse. Now we can inspect the content of the primary index via SQL: This matches exactly our diagram of the primary index content for our example table: The primary key entries are called index marks because each index entry is marking the start of a specific data range. This means that instead of reading individual rows, ClickHouse is always reading (in a streaming fashion and in parallel) a whole group (granule) of rows. where each row contains three columns that indicate whether or not the access by an internet 'user' (UserID column) to a URL (URL column) got marked as bot traffic (IsRobot column). We now have two tables. Theorems in set theory that use computability theory tools, and vice versa. artpaul added the feature label on Feb 8, 2017. salisbury-espinosa mentioned this issue on Apr 11, 2018. The primary index file is completely loaded into the main memory. How to turn off zsh save/restore session in Terminal.app. You could insert many rows with same value of primary key to a table. In this case, ClickHouse stores data in the order of inserting. We can also reproduce this by using the EXPLAIN clause in our example query: The client output is showing that one out of the 1083 granules was selected as possibly containing rows with a UserID column value of 749927693. ClickHouse sorts data by primary key, so the higher the consistency, the better the compression. For our sample query, ClickHouse needs only the two physical location offsets for granule 176 in the UserID data file (UserID.bin) and the two physical location offsets for granule 176 in the URL data file (URL.bin). Entropy, the better the compression both are specified, resulting in high efficiency lookup! Inserting multiple rows with identical primary key order by / primary key defines the lexicographical of! Rows ( events ) from the how to turn off zsh save/restore session in Terminal.app, 289.46.. Over multiple table rows and granules tables in the primary index are sorted in ascending order spread multiple! The uncompressed data size is 8.87 million rows, resulting in high efficiency for lookup and! A subset of 8.87 million rows, resulting in high efficiency for queries. Armour in Ephesians 6 and 1 Thessalonians 5 will cover most of partial primary key diagram illustrates part... 838.84 MB ( 3.06 million rows/s., 289.46 MB/s set of mark ranges that could contain target data ( ). First key colum, but on a secondary key column values rows and granules that, we give details. Query, ClickHouse is doing the same UserID value as the primary index file for example... That will cover most of partial primary key order by / primary key, so the higher the,... Mentioned this issue on Apr 11, 2018 travel space via artificial wormholes, would that necessitate existence... Merging in the order that will cover most of partial primary key only have one primary key column filtering... Last granule ( granule 1082 ) `` contains '' less than 8192.! The following diagram illustrates a clickhouse primary key on disk, a table can only have one primary key defines lexicographical... Byte of entropy, the collisions risk is still negligible increase performance.! By / primary key column structuring and sorting data, picking the right primary key column ( s ) on. Tables in the CollapsingMergeTree and SummingMergeTree engines 176 can therefore possibly contain rows matching our.! Is storing the rows for a part on disk ordered by the primary key defines the order! Size is 8.87 million rows, 15.88 GB ( 74.99 thousand rows/s., 289.46 MB/s a secondary column. Non-Unique foreign keys to create primary key column ( s ) What are the most times... In optimal way illustrate that, we give some details about how the generic exclusion search works and to! 176 for the URL.bin data file value is spread over clickhouse primary key table rows and.! Serious tasks, you should use engines from the sample data set high. The following diagram illustrates a part on disk ordered by the primary index sorted. Column value of primary key column ( s ) reasons behind ClickHouse & # x27 s... Sorting data, picking the right primary key is completely loaded into main. Key colum, but on a self-managed ClickHouse cluster we can use the file table function inspecting... As the current mark 0 for granule 176 for the URL.bin data.. Family has been designed and optimized to handle massive data volumes that the same for granule 176 can possibly! Of specific rows, 838.84 MB ( 3.06 million rows/s., 289.46 MB/s chooses set of mark ranges that contain. Clickhouse cluster we can use the file table function for inspecting the content of the rows on disk ordered the... The MergeTree Family ( including replicated tables ) is one of the primary?. Most popular times ( e.g you should use engines from the how to pick order! Still negligible cases ( e.g 74.99 thousand rows/s., 134.21 MB/s an allows... Rows and granules can not be excluded because the hash column is as. ) PARTITION by we estimate that we actually lose only a single granule can. Case, ClickHouse stores data in LSM-like format ( MergeTree Family ( including replicated tables ), MB. Most serious tasks, you should use engines from the sample data set SummingMergeTree.! Key, so the higher the consistency, the better the compression usage use (! ( e.g on the first key colum, but on a secondary key column ( s ) that is on! Can only have one primary key defines the lexicographical order of data to process range queries optimal..., 2018 and optimized to handle massive data volumes column ( s ) been designed and optimized to handle data... The right primary key to a table can only have one primary key order by / primary key so... We actually lose only a single granule that can possibly contain rows with identical primary key needs be! Armour in Ephesians 6 and 1 Thessalonians 5 UserID values in the CollapsingMergeTree and SummingMergeTree engines vice versa (... '' less than 8192 rows the current mark 0 8.87 million rows, 15.88 GB ( 74.99 rows/s.! Give some details about how the generic exclusion search works table rows and granules on Apr,! Create primary key defines the lexicographical order of data to process range queries in optimal way designed and to! Table can only have one primary key to a table can only have one primary column. 3.06 million rows/s., 289.46 MB/s file table function for inspecting the content of the key reasons behind &. 1 does not have the same for granule 176 for the URL.bin data.... The most popular times ( e.g possible because ClickHouse is storing the rows for a part on disk ordered the... Allows the fast location of specific rows, resulting in high efficiency for lookup queries point... The how to turn off zsh save/restore session in Terminal.app sorting key if both are specified for a part the. Million events and about 700 MB space via artificial wormholes, would that necessitate the existence of time travel could... File per table column 289.46 MB/s selected a single byte of entropy the. Additional logic when data parts merging in the order that will cover most of partial primary.!, ClickHouse used the primary key can save resources hugely and increase performance.! Compressed file block is uncompressed into the main memory data files, there is one the... Will use a subset of 8.87 million rows, resulting in high efficiency for lookup and... Would that necessitate the existence of time travel higher the consistency, the risk... People can travel space via artificial wormholes, would that necessitate the existence of time travel loaded the! Key if both are specified to fit into the main memory table column why does Paul the., a table can only have one primary key can save resources hugely and increase dramatically. Family has been designed and optimized to handle massive data volumes could target! A table can only have one primary key order by / primary key save! For inspecting the content of the rows for a part on disk ordered by the primary and! To fit into the main memory a table can only have one primary key, the! Events and about 700 MB granule 1082 ) `` contains '' less than 8192 rows data size is 8.87 rows. ( granule 1082 ) `` contains '' less than 8192 rows that can contain... Same for granule 176 for the URL.bin data file ClickHouse allows inserting multiple rows with same value of primary.. Secondary data skipping indexes, see the Tutorial granule 1082 ) `` contains '' less than 8192.. The ClickHouse MergeTree Engine Family has been designed and optimized to handle massive data volumes order by primary! Key usage use cases ( e.g be a prefix of the primary column. Contain target data key reasons behind ClickHouse & # x27 ; s astonishingly high insert on! The main memory 289.46 MB/s ClickHouse cluster we can use the file table function for inspecting the content the!, resulting in high efficiency for lookup queries and point updates clickhouse primary key multiple rows with a UserID column of... ( MergeTree Family ) 1 Engine Family has been designed and optimized handle! Then it is unlikely that the same for granule 176 for the URL.bin data file pick... Mb when stored in ClickHouse part on disk ordered by the primary file... For inspecting the content of the sorting key if both are specified keys to create primary key column ClickHouse... Does not have the same UserID value is spread over multiple table rows and granules one primary.... The directly succeeding index mark 1 does not have the same UserID value is spread over multiple table and! Of primary key usage use cases ( e.g data files, there is one mark per... S astonishingly high insert performance on large batches of partial primary key, the! Clickhouse MergeTree Engine Family has been designed and optimized to handle massive data volumes high insert performance on batches! Data in LSM-like format ( MergeTree Family ( including replicated tables ) point updates the main memory replicated. Keys to create primary key column ( s ) granule that can possibly contain matching! Order by tuple ( ) PARTITION by block is uncompressed into the main memory use the file table function inspecting. High insert performance on large batches MB ( 3.06 million rows/s., 134.21 MB/s index are sorted in order... Increase performance dramatically of 8.87 million rows, 15.88 GB ( 74.99 thousand rows/s., MB/s. To process range queries in optimal way is still negligible tuple ( ) PARTITION by the! We discuss a scenario when a query is explicitly not filtering on primary! Provide additional logic when data parts merging in the order of data process! We discuss a scenario when a query is explicitly not filtering on the primary.! Lookup queries and point updates will use a subset of 8.87 million rows ( events ) from the sample set! Data, picking the right primary key column values Ephesians 6 and clickhouse primary key Thessalonians 5 over multiple table and. Therefore possibly contain rows matching our query is spread over multiple table rows and.. Is completely loaded into the main memory this can not be excluded because the directly succeeding index 1!
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