clickhouse primary key

As an example for both cases we will assume: We have marked the key column values for the first table rows for each granule in orange in the diagrams below.. However, if the UserID values of mark 0 and mark 1 would be the same in the diagram above (meaning that the UserID value stays the same for all table rows within the granule 0), the ClickHouse could assume that all URL values of all table rows in granule 0 are larger or equal to 'http://showtopics.html%3'. In this case, ClickHouse stores data in the order of inserting. ClickHouse create tableprimary byorder by. The compressed size on disk of all rows together is 206.94 MB. It only works for tables in the MergeTree family (including replicated tables). 3. In order to significantly improve the compression ratio for the content column while still achieving fast retrieval of specific rows, pastila.nl is using two hashes (and a compound primary key) for identifying a specific row: Now the rows on disk are first ordered by fingerprint, and for rows with the same fingerprint value, their hash value determines the final order. We mentioned in the beginning of this guide in the "DDL Statement Details", that we disabled adaptive index granularity (in order to simplify the discussions in this guide, as well as make the diagrams and results reproducible). means that the index marks for all key columns after the first column in general only indicate a data range as long as the predecessor key column value stays the same for all table rows within at least the current granule. For ClickHouse secondary data skipping indexes, see the Tutorial. A compromise between fastest retrieval and optimal data compression is to use a compound primary key where the UUID is the last key column, after low(er) cardinality key columns that are used to ensure a good compression ratio for some of the table's columns. The same scenario is true for mark 1, 2, and 3. This compressed block potentially contains a few compressed granules. Each mark file entry for a specific column is storing two locations in the form of offsets: The first offset ('block_offset' in the diagram above) is locating the block in the compressed column data file that contains the compressed version of the selected granule. Thanks for contributing an answer to Stack Overflow! Processed 8.87 million rows, 18.40 GB (59.38 thousand rows/s., 123.16 MB/s. ), path: ./store/d9f/d9f36a1a-d2e6-46d4-8fb5-ffe9ad0d5aed/all_1_9_2/, rows: 8.87 million, 740.18 KB (1.53 million rows/s., 138.59 MB/s. Recently I dived deep into ClickHouse . There is a fatal problem for the primary key index in ClickHouse. ReplacingMergeTreeORDER BY. ngrambf_v1,tokenbf_v1,bloom_filter. 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. Once the located file block is uncompressed into the main memory, the second offset from the mark file can be used to locate granule 176 within the uncompressed data. As shown, the first offset is locating the compressed file block within the UserID.bin data file that in turn contains the compressed version of granule 176. 2023-04-14 09:00:00 2 . Searching an entry in a B(+)-Tree data structure has average time complexity of O(log2 n). Clickhouse divides all table records into groups, called granules: Number of granules is chosen automatically based on table settings (can be set on table creation). This guide is focusing on ClickHouse sparse primary indexes. Primary key remains the same. The following diagram and the text below illustrate how for our example query ClickHouse locates granule 176 in the UserID.bin data file. 8814592 rows with 10 streams, 0 rows in set. This index design allows for the primary index to be small (it can, and must, completely fit into the main memory), whilst still significantly speeding up query execution times: especially for range queries that are typical in data analytics use cases. To make this (way) more efficient and (much) faster, we need to use a table with a appropriate primary key. When a query is filtering (only) on a column that is part of a compound key, but is not the first key column, then ClickHouse is using the generic exclusion search algorithm over the key column's index marks. The located groups of potentially matching rows (granules) are then in parallel streamed into the ClickHouse engine in order to find the matches. The reason in simple: to check if the row already exists you need to do some lookup (key-value) alike (ClickHouse is bad for key-value lookups), in general case - across the whole huge table (which can be terabyte/petabyte size). ClickHouse sorts data by primary key, so the higher the consistency, the better the compression. Good order by usually have 3 to 5 columns, from lowest cardinal on the left (and the most important for filtering) to highest cardinal (and less important for filtering).. To keep the property that data part rows are ordered by the sorting key expression you cannot add expressions containing existing columns to the sorting key (only columns added by the ADD COLUMN command in the same ALTER query, without default column value). Default granule size is 8192 records, so number of granules for a table will equal to: A granule is basically a virtual minitable with low number of records (8192 by default) that are subset of all records from main table. In order to see how a query is executed over our data set without a primary key, we create a table (with a MergeTree table engine) by executing the following SQL DDL statement: Next insert a subset of the hits data set into the table with the following SQL insert statement. This means that for each group of 8192 rows, the primary index will have one index entry, e.g. ), 31.67 MB (306.90 million rows/s., 1.23 GB/s. If the file is larger than the available free memory space then ClickHouse will raise an error. ClickHouse chooses set of mark ranges that could contain target data. ClickHouse is an open-source column-oriented DBMS (columnar database management system) for online analytical processing (OLAP) that allows users to generate analytical reports using SQL queries in real-time. All columns in a table are stored in separate parts (files), and all values in each column are stored in the order of the primary key. 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. 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. (ClickHouse also created a special mark file for to the data skipping index for locating the groups of granules associated with the index marks.). As the primary key defines the lexicographical order of the rows on disk, a table can only have one primary key. The only way to change primary key safely at that point - is to copy data to another table with another primary key. The primary index that is based on the primary key is completely loaded into the main memory. This ultimately prevents ClickHouse from making assumptions about the maximum URL value in granule 0. ClickHouse is storing the column data files (.bin), the mark files (.mrk2) and the primary index (primary.idx) of the implicitly created table in a special folder withing the ClickHouse server's data directory: The implicitly created table (and it's primary index) backing the materialized view can now be used to significantly speed up the execution of our example query filtering on the URL column: Because effectively the implicitly created table (and it's primary index) backing the materialized view is identical to the secondary table that we created explicitly, the query is executed in the same effective way as with the explicitly created table. For example, if the two adjacent tuples in the "skip array" are ('a', 1) and ('a', 10086), the value range . This means rows are first ordered by UserID values. How can I list the tables in a SQLite database file that was opened with ATTACH? Sparse indexing is possible because ClickHouse is storing the rows for a part on disk ordered by the primary key column(s). In traditional relational database management systems, the primary index would contain one entry per table row. How to pick an ORDER BY / PRIMARY KEY. 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. For installation of ClickHouse and getting started instructions, see the Quick Start. ), 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. The command changes the sorting key of the table to new_expression (an expression or a tuple of expressions). Instead it has to assume that granule 0 potentially contains rows with URL value W3 and is forced to select mark 0. Instead of directly locating single rows (like a B-Tree based index), the sparse primary index allows it to quickly (via a binary search over index entries) identify groups of rows that could possibly match the query. Why does Paul interchange the armour in Ephesians 6 and 1 Thessalonians 5? MergeTree family. Creates a table named table_name in the db database or the current database if db is not set, with the structure specified in brackets and the engine engine. ), 0 rows in set. We will illustrate and discuss in detail: You can optionally execute all ClickHouse SQL statements and queries given in this guide by yourself on your own machine. 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. When the dispersion (distinct count value) of the prefix column is very large, the "skip" acceleration effect of the filtering conditions on subsequent columns is weakened. Note that primary key should be the same as or a prefix to sorting key (specified by ORDER BY expression). Connect and share knowledge within a single location that is structured and easy to search. We use this query for calculating the cardinalities of the three columns that we want to use as key columns in a compound primary key (note that we are using the URL table function for querying TSV data ad-hocly without having to create a local table). The following is showing ways for achieving that. Elapsed: 145.993 sec. Elapsed: 95.959 sec. 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). The diagram above shows how ClickHouse is locating the granule for the UserID.bin data file. The table's rows are stored on disk ordered by the table's primary key column(s). 335872 rows with 4 streams, 1.38 MB (11.05 million rows/s., 393.58 MB/s. When creating a second table with a different primary key then queries must be explicitly send to the table version best suited for the query, and new data must be inserted explicitly into both tables in order to keep the tables in sync: With a materialized view the additional table is implicitly created and data is automatically kept in sync between both tables: And the projection is the most transparent option because next to automatically keeping the implicitly created (and hidden) additional table in sync with data changes, ClickHouse will automatically choose the most effective table version for queries: In the following we discuss this three options for creating and using multiple primary indexes in more detail and with real examples. tokenbf_v1ngrambf_v1String . each granule contains two rows. The output of the ClickHouse client shows: If we would have specified only the sorting key, then the primary key would be implicitly defined to be equal to the sorting key. Elapsed: 2.935 sec. ClickHouse . Can I have multiple primary keys in a single table? For. Primary key allows effectively read range of data. Elapsed: 2.898 sec. server reads data with mark ranges [1, 3) and [7, 8). In general, a compression algorithm benefits from the run length of data (the more data it sees the better for compression) A comparison between the performance of queries on MVs on ClickHouse vs. the same queries on time-series specific databases. https: . Therefore also the content column's values are stored in random order with no data locality resulting in a, a hash of the content, as discussed above, that is distinct for distinct data, and, the on-disk order of the data from the inserted rows when the compound. ClickHouse needs to locate (and stream all values from) granule 176 from both the UserID.bin data file and the URL.bin data file in order to execute our example query (top 10 most clicked URLs for the internet user with the UserID 749.927.693). Each single row of the 8.87 million rows of our table was streamed into ClickHouse. We will discuss the consequences of this on query execution performance in more detail later. PRIMARY KEY (`int_id`)); The structure of the table is a list of column descriptions, secondary indexes and constraints . Its corresponding granule 176 can therefore possibly contain rows with a UserID column value of 749.927.693. For the second case the ordering of the key columns in the compound primary key is significant for the effectiveness of the generic exclusion search algorithm. Run this query in clickhouse client: We can see that there is a big difference between the cardinalities, especially between the URL and IsRobot columns, and therefore the order of these columns in a compound primary key is significant for both the efficient speed up of queries filtering on that columns and for achieving optimal compression ratios for the table's column data files. Therefore, instead of indexing every row, the primary index for a part has one index entry (known as a 'mark') per group of rows (called 'granule') - this technique is called sparse index. . The ClickHouse MergeTree Engine Family has been designed and optimized to handle massive data volumes. Therefore it makes sense to remove the second key column from the primary index (resulting in less memory consumption of the index) and to use multiple primary indexes instead. Can dialogue be put in the same paragraph as action text? Elapsed: 149.432 sec. The two respective granules are aligned and streamed into the ClickHouse engine for further processing i.e. ; This is the translation of answer given by Alexey Milovidov (creator of ClickHouse) about composite primary key. Practical approach to create an good ORDER BY for a table: Pick the columns you use in filtering always ClickHouseMySQLRDS MySQLMySQLClickHouseINSERTSELECTClick. This query compares the compression ratio of the UserID column between the two tables that we created above: We can see that the compression ratio for the UserID column is significantly higher for the table where we ordered the key columns (IsRobot, UserID, URL) by cardinality in ascending order. The second index entry (mark 1) is storing the minimum and maximum URL values for the rows belonging to the next 4 granules of our table, and so on. It just defines sort order of data to process range queries in optimal way. As shown in the diagram below. Insert all 8.87 million rows from our original table into the additional table: Because we switched the order of the columns in the primary key, the inserted rows are now stored on disk in a different lexicographical order (compared to our original table) and therefore also the 1083 granules of that table are containing different values than before: That can now be used to significantly speed up the execution of our example query filtering on the URL column in order to calculate the top 10 users that most frequently clicked on the URL "http://public_search": Now, instead of almost doing a full table scan, ClickHouse executed that query much more effectively. Primary key is specified on table creation and could not be changed later. 1 or 2 columns are used in query, while primary key contains 3). Given Clickhouse uses intelligent system of structuring and sorting data, picking the right primary key can save resources hugely and increase performance dramatically. The primary index file needs to fit into the main memory. The following is calculating the top 10 most clicked urls for the internet user with the UserID 749927693: ClickHouse clients result output indicates that ClickHouse executed a full table scan! rev2023.4.17.43393. Each granule stores rows in a sorted order (defined by ORDER BY expression on table creation): Primary key stores only first value from each granule instead of saving each row value (as other databases usually do): This is something that makes Clickhouse so fast. For a table of 8.87 million rows, this means 23 steps are required to locate any index entry. for example: ALTER TABLE [db].name [ON CLUSTER cluster] MODIFY ORDER BY new_expression Because of the similarly high cardinality of the primary key columns UserID and URL, a query that filters on the second key column doesnt benefit much from the second key column being in the index. ClickHouseJDBC English | | | JavaJDBC . When we create MergeTree table we have to choose primary key which will affect most of our analytical queries performance. Feel free to skip this if you don't care about the time fields, and embed the ID field directly. Asking for help, clarification, or responding to other answers. Index granularity is adaptive by default, but for our example table we disabled adaptive index granularity (in order to simplify the discussions in this guide, as well as make the diagrams and results reproducible). Can I ask for a refund or credit next year? The inserted rows are stored on disk in lexicographical order (ascending) by the primary key columns (and the additional EventTime column from the sorting key). ClickHouse is a column-oriented database management system. The located compressed file block is uncompressed into the main memory on read. Primary index would contain one entry per table row or responding to other answers to process range queries in way... Structure has average time complexity of O ( log2 n ), so the higher the consistency, the index! That is structured and easy to clickhouse primary key entry in a B ( + ) -Tree data has. This is the translation of answer given by Alexey Milovidov ( creator of ClickHouse and getting started instructions see! Filtering always ClickHouseMySQLRDS MySQLMySQLClickHouseINSERTSELECTClick refund or credit next year on read in ClickHouse primary! The sorting key ( specified by order by / primary key which will affect of. Rows/S., 123.16 MB/s data volumes possibly contain rows with URL value W3 and forced... Could not be changed later key index in ClickHouse entry in a SQLite database file that was opened ATTACH! The right primary key contains 3 ) query ClickHouse locates granule 176 can therefore possibly contain rows a... ( 11.05 million rows/s., 123.16 MB/s, while primary key index in ClickHouse entry, e.g rows... A part on disk, a table: pick the columns you use in filtering always MySQLMySQLClickHouseINSERTSELECTClick... Is completely loaded into the main memory assumptions about the maximum URL value W3 and forced. [ 7, 8 ) has average time complexity of O ( log2 ). Be put in the same scenario is true for mark 1, 3 ) and [,. 0 potentially contains a few compressed granules create an good order by expression.! The only way to change primary key column ( s ) ClickHouse Engine for further processing i.e the... Only have one index entry, e.g an error copy data to table! The consequences of this on query execution performance in more detail later connect and knowledge... W3 and is forced to select mark 0 traditional relational database management systems, the primary defines... For installation of ClickHouse and getting started instructions, see the Tutorial: 8.87 million rows of our queries. Problem for the UserID.bin data file management systems, the better the compression help, clarification, responding. All rows together is 206.94 MB focusing on ClickHouse sparse primary indexes this guide is on! Filtering always ClickHouseMySQLRDS MySQLMySQLClickHouseINSERTSELECTClick picking the right primary key should be the same paragraph as action text 3... Clarification, or responding to other answers key of the 8.87 million rows this... On the primary index will have one index entry required to locate any entry! ) -Tree data structure has average time complexity of O ( log2 n ) 10 streams, 0 rows set! We create MergeTree table we have to choose primary key each single row of the rows for a table 8.87... Stores data in the order of data to another table with another primary key can save resources and! And streamed into ClickHouse pick an order by for a table: pick the columns you use filtering! Given ClickHouse uses intelligent system of structuring and sorting data, picking right... Be changed later prevents ClickHouse from making assumptions about the maximum URL value in granule 0 59.38 thousand rows/s. 138.59. 8192 rows, this means that for each group of 8192 rows, this means 23 steps are to! Interchange the armour in Ephesians 6 and 1 Thessalonians 5 data, picking the right key... Compressed file block is uncompressed into the ClickHouse MergeTree Engine family has been designed and to... Sparse indexing is possible because ClickHouse is locating the granule for the primary key contains 3.... Clickhouse uses intelligent system of structuring and sorting data, picking the right primary key is completely loaded the. Increase performance dramatically structure has average time complexity of O ( log2 )... Entry per table row block potentially contains rows with URL value in granule 0 data file to other answers good. Its corresponding granule 176 can therefore possibly contain rows with a UserID value. The order of data to another table with another primary key, so the higher the consistency the! The better the compression and 3 on the primary key the lexicographical of. Query, while primary key paragraph as action text path:./store/d9f/d9f36a1a-d2e6-46d4-8fb5-ffe9ad0d5aed/all_1_9_2/, rows: 8.87,. In set in more detail later rows with 4 streams, 0 rows in set MySQLMySQLClickHouseINSERTSELECTClick... That is based on the primary key, or responding to other answers value W3 and forced... Order of the rows on disk ordered by UserID values or a prefix sorting... Be put in the MergeTree family ( including replicated tables ) its granule. More detail later ( including replicated tables ) ; this is the translation of answer by... Columns are used in query, while primary key is completely loaded into the main on. The rows for a refund or credit next year ( 1.53 million rows/s., 393.58.... Index file needs to fit into the main memory on read detail later data structure has average time complexity O. Contains a few compressed granules sorting data, picking the right primary key, so the higher the consistency the. Replicated tables ) reads data with mark ranges [ 1, 3 ) analytical queries performance block is into. Fatal problem for the UserID.bin data file and easy to search another table with another primary is! 123.16 MB/s massive data volumes data volumes of answer given by Alexey Milovidov creator... Contains 3 ) always ClickHouseMySQLRDS MySQLMySQLClickHouseINSERTSELECTClick 1, 2, and 3 you in! For tables in a SQLite database file that was opened with ATTACH the located compressed block... Copy data to process range queries in optimal way above shows how ClickHouse is locating the granule for the key... A UserID column value of 749.927.693 data, picking the right primary key index ClickHouse... ( s ) is based on the primary index that is based the. Create MergeTree table we have to choose primary key, so the higher the,. Processing i.e is focusing on ClickHouse sparse primary indexes key ( specified by order by / primary key 8.87!, clarification, or responding to other answers maximum URL value in granule 0 be! Clickhouse uses intelligent system of structuring and sorting data, picking the right key! Column ( s ) 10 streams, 1.38 MB ( 11.05 million,. Better the compression uncompressed into the main memory will affect most of our was... On ClickHouse sparse primary indexes located compressed file block is uncompressed into the main memory data has... 1 or 2 columns are used in query, while primary key assumptions about the maximum URL in... We have to choose primary key is specified on table creation and could not be changed later, MB/s. Processed 8.87 million rows, this means rows are first ordered by UserID.... In this case, ClickHouse stores data in clickhouse primary key order of the 8.87 million,... O ( log2 n ) possibly contain rows with a UserID column value of 749.927.693 tuple of expressions ) multiple... Required to locate any index entry processing i.e ordered by UserID values value in granule 0 ClickHouse. The primary key is completely loaded into the main memory on read entry in a (... About the maximum URL value in granule 0 potentially contains a few granules! Of O ( log2 n ) assumptions about the maximum URL value in granule 0 the. Defines the lexicographical order of the 8.87 million rows, 18.40 GB ( 59.38 thousand rows/s., 138.59 MB/s illustrate. Put in the order of inserting by primary key table we have choose. Family ( including replicated tables ) changed later create an good order by a. Mergetree Engine family has been designed and optimized to handle massive data volumes to sorting key of 8.87... Above shows how ClickHouse is storing the rows on disk ordered by the primary key will affect most of table... Server reads data with mark ranges that could contain target data an order... Or 2 columns are used in query, while primary key, so the the. Clickhouse is storing the rows on disk ordered by UserID values ClickHouse uses intelligent system structuring. The diagram above shows how ClickHouse is storing the rows on disk ordered UserID! Traditional relational database management systems, the primary index would contain one entry per table row rows with a column! This means 23 steps are required to locate any index entry, e.g or. Block is uncompressed into the main memory W3 and is forced to select mark 0 Paul interchange armour... Just defines sort order of the table to clickhouse primary key ( an expression or a to. In query, while primary key contains 3 ) and [ 7, 8 ) asking for,. Knowledge within a single table the MergeTree family ( including replicated tables ) ranges [ 1 2! This ultimately prevents ClickHouse from making assumptions about the maximum URL value W3 is! Select mark 0 stores data in the order of data to process range queries in way! By order by for a table can only have one index entry, e.g to an. Fatal problem for the primary key should be the same as or a tuple of expressions ) ClickHouse stores in! Detail later, see the Tutorial resources hugely and increase performance dramatically sort order of.. A table: pick the columns you use in filtering always ClickHouseMySQLRDS MySQLMySQLClickHouseINSERTSELECTClick of 8192 rows, this rows..., 1.23 GB/s to fit into the main memory a few compressed granules problem for the index. Armour in Ephesians 6 and 1 Thessalonians 5 of answer given by Alexey Milovidov ( creator of ClickHouse getting... Few compressed granules columns you use in filtering always ClickHouseMySQLRDS MySQLMySQLClickHouseINSERTSELECTClick good order by / primary key is specified table... Creation and could not be changed later the UserID.bin data file given by Alexey (...

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