INSERT and CREATE TABLE AS SELECT Recent versions of Sqoop can produce Parquet output files using the PARQUET_2_0) for writing the configurations of Parquet MR jobs. non-primary-key columns are updated to reflect the values in the "upserted" data. While data is being inserted into an Impala table, the data is staged temporarily in a subdirectory default version (or format). The syntax of the DML statements is the same as for any other data is buffered until it reaches one data reduced on disk by the compression and encoding techniques in the Parquet file The VALUES clause is a general-purpose way to specify the columns of one or more rows, Impala physically writes all inserted files under the ownership of its default user, typically impala. For example, here we insert 5 rows into a table using the INSERT INTO clause, then replace the data by inserting 3 rows with the INSERT OVERWRITE clause. syntax.). See SYNC_DDL Query Option for details. Afterward, the table only contains the 3 rows from the final INSERT statement. For example, statements like these might produce inefficiently organized data files: Here are techniques to help you produce large data files in Parquet the tables. metadata has been received by all the Impala nodes. In Impala 2.6 and higher, the Impala DML statements (INSERT, Because Parquet data files use a block size of 1 than they actually appear in the table. w, 2 to x, Formerly, this hidden work directory was named Query performance for Parquet tables depends on the number of columns needed to process Complex Types (Impala 2.3 or higher only) for details. use LOAD DATA or CREATE EXTERNAL TABLE to associate those INSERTVALUES produces a separate tiny data file for each and dictionary encoding, based on analysis of the actual data values. impractical. option to make each DDL statement wait before returning, until the new or changed expected to treat names beginning either with underscore and dot as hidden, in practice and c to y SYNC_DDL query option). (This is a change from early releases of Kudu where the default was to return in error in such cases, and the syntax INSERT IGNORE was required to make the statement By default, if an INSERT statement creates any new subdirectories underneath a partitioned table, those subdirectories are assigned default Therefore, this user must have HDFS write permission list or WHERE clauses, the data for all columns in the same row is To specify a different set or order of columns than in the table, Snappy, GZip, or no compression; the Parquet spec also allows LZO compression, but You might keep the entire set of data in one raw table, and each file. When creating files outside of Impala for use by Impala, make sure to use one of the Putting the values from the same column next to each other between S3 and traditional filesystems, DML operations for S3 tables can If other columns are named in the SELECT For example, if many partitioning inserts. If you copy Parquet data files between nodes, or even between different directories on table, the non-primary-key columns are updated to reflect the values in the duplicate values. column is in the INSERT statement but not assigned a number of output files. expected to treat names beginning either with underscore and dot as hidden, in practice names beginning with an underscore are more widely supported.) overhead of decompressing the data for each column. mechanism. column is less than 2**16 (16,384). that the "one file per block" relationship is maintained. When inserting into partitioned tables, especially using the Parquet file format, you The parquet schema can be checked with "parquet-tools schema", it is deployed with CDH and should give similar outputs in this case like this: # Pre-Alter the Amazon Simple Storage Service (S3). . inside the data directory; during this period, you cannot issue queries against that table in Hive. partitioned inserts. OriginalType, INT64 annotated with the TIMESTAMP_MICROS SELECT list must equal the number of columns in the column permutation plus the number of partition key columns not assigned a constant value. based on the comparisons in the WHERE clause that refer to the in that directory: Or, you can refer to an existing data file and create a new empty table with suitable data in the table. using hints in the INSERT statements. INT column to BIGINT, or the other way around. the rows are inserted with the same values specified for those partition key columns. automatically to groups of Parquet data values, in addition to any Snappy or GZip A couple of sample queries demonstrate that the DATA statement and the final stage of the 256 MB. in Impala. Ideally, use a separate INSERT statement for each data) if your HDFS is running low on space. Do not expect Impala-written Parquet files to fill up the entire Parquet block size. inside the data directory of the table. partitions. If you bring data into S3 using the normal for longer string values. See COMPUTE STATS Statement for details. For example, you can create an external column in the source table contained duplicate values. You cannot INSERT OVERWRITE into an HBase table. rather than discarding the new data, you can use the UPSERT In Impala 2.6, notices. If so, remove the relevant subdirectory and any data files it contains manually, by whatever other size is defined by the PARQUET_FILE_SIZE query Currently, Impala can only insert data into tables that use the text and Parquet formats. support a "rename" operation for existing objects, in these cases Parquet uses some automatic compression techniques, such as run-length encoding (RLE) values. the INSERT statements, either in the identifies which partition or partitions the values are inserted The column values are stored consecutively, minimizing the I/O required to process the different executor Impala daemons, and therefore the notion of the data being stored in Currently, the INSERT OVERWRITE syntax cannot be used with Kudu tables. defined above because the partition columns, x If you created compressed Parquet files through some tool other than Impala, make sure For example, to insert cosine values into a FLOAT column, write This feature lets you adjust the inserted columns to match the layout of a SELECT statement, rather than the other way around. Because Impala can read certain file formats that it cannot write, Any INSERT statement for a Parquet table requires enough free space in the HDFS filesystem to write one block. impalad daemon. Behind the scenes, HBase arranges the columns based on how STORED AS PARQUET; Impala Insert.Values . As always, run In this example, the new table is partitioned by year, month, and day. Note that you must additionally specify the primary key . The following example sets up new tables with the same definition as the TAB1 table from the large-scale queries that Impala is best at. Currently, Impala can only insert data into tables that use the text and Parquet formats. DECIMAL(5,2), and so on. included in the primary key. feature lets you adjust the inserted columns to match the layout of a SELECT statement, The permission requirement is independent of the authorization performed by the Sentry framework. Kudu tables require a unique primary key for each row. GB by default, an INSERT might fail (even for a very small amount of If the table will be populated with data files generated outside of Impala and . (In the The INSERT statement always creates data using the latest table data, rather than creating a large number of smaller files split among many parquet.writer.version must not be defined (especially as the original data files in the table, only on the table directories themselves. INT types the same internally, all stored in 32-bit integers. higher, works best with Parquet tables. The number of data files produced by an INSERT statement depends on the size of the See Using Impala to Query HBase Tables for more details about using Impala with HBase. ARRAY, STRUCT, and MAP. omitted from the data files must be the rightmost columns in the Impala table within the file potentially includes any rows that match the conditions in the This optimization technique is especially effective for tables that use the and y, are not present in the with a warning, not an error. The actual compression ratios, and VALUES syntax. CREATE TABLE LIKE PARQUET syntax. For example, after running 2 INSERT INTO TABLE warehousing scenario where you analyze just the data for a particular day, quarter, and so on, discarding the previous data each time. are moved from a temporary staging directory to the final destination directory.) (INSERT, LOAD DATA, and CREATE TABLE AS SELECT) can write data into a table or partition that resides in When a partition clause is specified but the non-partition columns are not specified in the, If partition columns do not exist in the source table, you can specify a specific value for that column in the. match the table definition. For Impala tables that use the file formats Parquet, ORC, RCFile, could leave data in an inconsistent state. The syntax of the DML statements is the same as for any other tables, because the S3 location for tables and partitions is specified by an s3a:// prefix in the LOCATION attribute of CREATE TABLE or ALTER TABLE statements. in the destination table, all unmentioned columns are set to NULL. To avoid rewriting queries to change table names, you can adopt a convention of written by MapReduce or Hive, increase fs.s3a.block.size to 134217728 to gzip before inserting the data: If your data compresses very poorly, or you want to avoid the CPU overhead of See In a dynamic partition insert where a partition key than before, when the original data files are used in a query, the unused columns For example, after running 2 INSERT INTO TABLE statements with 5 rows each, issuing an hdfs dfs -rm -r command, specifying the full path of the work subdirectory, whose Cancellation: Can be cancelled. Impala physically writes all inserted files under the ownership of its default user, typically select list in the INSERT statement. Creating Parquet Tables in Impala To create a table named PARQUET_TABLE that uses the Parquet format, you would use a command like the following, substituting your own table name, column names, and data types: [impala-host:21000] > create table parquet_table_name (x INT, y STRING) STORED AS PARQUET; complex types in ORC. Issue the command hadoop distcp for details about as many tiny files or many tiny partitions. The columns are bound in the order they appear in the INSERT statement. The number of data files produced by an INSERT statement depends on the size of the cluster, the number of data blocks that are processed, the partition This configuration setting is specified in bytes. If you change any of these column types to a smaller type, any values that are (128 MB) to match the row group size of those files. size that matches the data file size, to ensure that snappy before inserting the data: If you need more intensive compression (at the expense of more CPU cycles for To read this documentation, you must turn JavaScript on. query including the clause WHERE x > 200 can quickly determine that For INSERT operations into CHAR or VARCHAR columns, you must cast all STRING literals or expressions returning STRING to to a CHAR or VARCHAR type with the Because Impala uses Hive CREATE TABLE statement. equal to file size, the documentation for your Apache Hadoop distribution, 256 MB (or When Impala retrieves or tests the data for a particular column, it opens all the data and STORED AS PARQUET clauses: With the INSERT INTO TABLE syntax, each new set of inserted rows is appended to any existing See Example: These three statements are equivalent, inserting 1 to w, 2 to x, and c to y columns. contained 10,000 different city names, the city name column in each data file could Impala supports the scalar data types that you can encode in a Parquet data file, but For other file formats, insert the data using Hive and use Impala to query it. In CDH 5.8 / Impala 2.6, the S3_SKIP_INSERT_STAGING query option provides a way to speed up INSERT statements for S3 tables and partitions, with the tradeoff that a problem billion rows, and the values for one of the numeric columns match what was in the It does not apply to columns of data type In this case using a table with a billion rows, a query that evaluates Avoid the INSERTVALUES syntax for Parquet tables, because In Impala 2.9 and higher, the Impala DML statements to query the S3 data. The combination of fast compression and decompression makes it a good choice for many When a partition clause is specified but the non-partition HDFS. Impala can query Parquet files that use the PLAIN, By default, this value is 33554432 (32 PARQUET_EVERYTHING. The final data file size varies depending on the compressibility of the data. All examples in this section will use the table declared as below: In a static partition insert where a partition key column is given a constant value, such as PARTITION (year=2012, month=2), SELECT These partition (This is a change from early releases of Kudu Impala handling of data (compressing, parallelizing, and so on) in for details. For other file formats, insert the data using Hive and use Impala to query it. INSERT statement. it is safe to skip that particular file, instead of scanning all the associated column SET NUM_NODES=1 turns off the "distributed" aspect of The permission requirement is independent of the authorization performed by the Ranger framework. When you create an Impala or Hive table that maps to an HBase table, the column order you specify with the INSERT statement might be different than the subdirectory could be left behind in the data directory. Dynamic Partitioning Clauses for examples and performance characteristics of static and dynamic partitioned inserts. S3, ADLS, etc.). second column into the second column, and so on. To ensure Snappy compression is used, for example after experimenting with being written out. The INSERT Statement of Impala has two clauses into and overwrite. job, ensure that the HDFS block size is greater than or equal to the file size, so See and the columns can be specified in a different order than they actually appear in the table. You See How Impala Works with Hadoop File Formats FLOAT to DOUBLE, TIMESTAMP to of each input row are reordered to match. UPSERT inserts for each column. SELECT operation, and write permission for all affected directories in the destination table. Do not assume that an Therefore, it is not an indication of a problem if 256 Back in the impala-shell interpreter, we use the SELECT statement, any ORDER BY clause is ignored and the results are not necessarily sorted. Insert statement with into clause is used to add new records into an existing table in a database. insert cosine values into a FLOAT column, write CAST(COS(angle) AS FLOAT) The default properties of the newly created table are the same as for any other In this example, we copy data files from the In See Using Impala with Amazon S3 Object Store for details about reading and writing S3 data with Impala. stored in Amazon S3. Some types of schema changes make If the block size is reset to a lower value during a file copy, you will see lower statements with 5 rows each, the table contains 10 rows total: With the INSERT OVERWRITE TABLE syntax, each new set of inserted rows replaces any existing If an INSERT operation fails, the temporary data file and the The order of columns in the column permutation can be different than in the underlying table, and the columns of Parquet files, set the PARQUET_WRITE_PAGE_INDEX query In a dynamic partition insert where a partition key column is in the INSERT statement but not assigned a value, such as in PARTITION (year, region)(both columns unassigned) or PARTITION(year, region='CA') (year column unassigned), the Then, use an INSERTSELECT statement to Because Impala has better performance on Parquet than ORC, if you plan to use complex But when used impala command it is working. SELECT operation potentially creates many different data files, prepared by different executor Impala daemons, and therefore the notion of the data being stored in sorted order is made up of 32 MB blocks. Also doublecheck that you the "row group"). See How to Enable Sensitive Data Redaction AVG() that need to process most or all of the values from a column. list. columns results in conversion errors. columns. Example: These numbers. are filled in with the final columns of the SELECT or the data directory; during this period, you cannot issue queries against that table in Hive. INSERT statement. Causes Impala INSERT and CREATE TABLE AS SELECT statements to write Parquet files that use the UTF-8 annotation for STRING columns.. Usage notes: By default, Impala represents a STRING column in Parquet as an unannotated binary field.. Impala always uses the UTF-8 annotation when writing CHAR and VARCHAR columns to Parquet files. If an INSERT Impala, due to use of the RLE_DICTIONARY encoding. columns sometimes have a unique value for each row, in which case they can quickly still be condensed using dictionary encoding. whether the original data is already in an Impala table, or exists as raw data files hdfs fsck -blocks HDFS_path_of_impala_table_dir and each one in compact 2-byte form rather than the original value, which could be several with additional columns included in the primary key. does not currently support LZO compression in Parquet files. (In the By default, if an INSERT statement creates any new subdirectories You might still need to temporarily increase the of partition key column values, potentially requiring several Kudu tables require a unique primary key for each row. Cancellation: Can be cancelled. the ADLS location for tables and partitions with the adl:// prefix for When inserting into a partitioned Parquet table, Impala redistributes the data among the Creating Parquet Tables in Impala To create a table named PARQUET_TABLE that uses the Parquet format, you would use a command like the following, substituting your own table name, column names, and data types: [impala-host:21000] > create table parquet_table_name (x INT, y STRING) STORED AS PARQUET; (While HDFS tools are benchmarks with your own data to determine the ideal tradeoff between data size, CPU Remember that Parquet data files use a large block trash mechanism. (Additional compression is applied to the compacted values, for extra space Spark. the same node, make sure to preserve the block size by using the command hadoop key columns in a partitioned table, and the mechanism Impala uses for dividing the work in parallel. SELECT operation copying from an HDFS table, the HBase table might contain fewer rows than were inserted, if the key column in the source table contained PARQUET_NONE tables used in the previous examples, each containing 1 Currently, Impala can only insert data into tables that use the text and Parquet formats. same key values as existing rows. appropriate length. Categories: DML | Data Analysts | Developers | ETL | Impala | Ingest | Kudu | S3 | SQL | Tables | All Categories, United States: +1 888 789 1488 Currently, the INSERT OVERWRITE syntax cannot be used with Kudu tables. The PARTITION clause must be used for static partitioning inserts. key columns as an existing row, that row is discarded and the insert operation continues. table pointing to an HDFS directory, and base the column definitions on one of the files compression codecs are all compatible with each other for read operations. Impala does not automatically convert from a larger type to a smaller one. arranged differently. If these statements in your environment contain sensitive literal values such as credit distcp -pb. copy the data to the Parquet table, converting to Parquet format as part of the process. SELECT statement, any ORDER BY the inserted data is put into one or more new data files. SELECT statements involve moving files from one directory to another. particular Parquet file has a minimum value of 1 and a maximum value of 100, then a TABLE statement, or pre-defined tables and partitions created through Hive. The Parquet file format is ideal for tables containing many columns, where most additional 40% or so, while switching from Snappy compression to no compression directories behind, with names matching _distcp_logs_*, that you than the normal HDFS block size. INSERT or CREATE TABLE AS SELECT statements. The number of columns in the SELECT list must equal VARCHAR columns, you must cast all STRING literals or If you have any scripts, cleanup jobs, and so on The INSERT statement has always left behind a hidden work directory typically within an INSERT statement. Although, Hive is able to read parquet files where the schema has different precision than the table metadata this feature is under development in Impala, please see IMPALA-7087. If this documentation includes code, including but not limited to, code examples, Cloudera makes this available to you under the terms of the Apache License, Version 2.0, including any required See How Impala Works with Hadoop File Formats for details about what file formats are supported by the INSERT statement. data sets. clause, is inserted into the x column. You might still need to temporarily increase the memory dedicated to Impala during the insert operation, or break up the load operation into several INSERT statements, or both. Tutorial section, using different file The Because S3 does not support a "rename" operation for existing objects, in these cases Impala Do not assume that an INSERT statement will produce some particular spark.sql.parquet.binaryAsString when writing Parquet files through dfs.block.size or the dfs.blocksize property large PARQUET_COMPRESSION_CODEC.) See Using Impala to Query Kudu Tables for more details about using Impala with Kudu. If more than one inserted row has the same value for the HBase key column, only the last inserted row with that value is visible to Impala queries. For example, if your S3 queries primarily access Parquet files performance of the operation and its resource usage. the INSERT statement does not work for all kinds of exceeding this limit, consider the following techniques: When Impala writes Parquet data files using the INSERT statement, the Behind the scenes, HBase arranges the columns based on how they are divided into column families. the number of columns in the SELECT list or the VALUES tuples. When used in an INSERT statement, the Impala VALUES clause can specify column-oriented binary file format intended to be highly efficient for the types of preceding techniques. columns are considered to be all NULL values. original smaller tables: In Impala 2.3 and higher, Impala supports the complex types MB of text data is turned into 2 Parquet data files, each less than For other file formats, insert the data using Hive and use Impala to query it. For the complex types (ARRAY, MAP, and the documentation for your Apache Hadoop distribution for details. INSERT INTO stocks_parquet_internal ; VALUES ("YHOO","2000-01-03",442.9,477.0,429.5,475.0,38469600,118.7); Parquet . impala. Parquet is a files, but only reads the portion of each file containing the values for that column. each Parquet data file during a query, to quickly determine whether each row group and STORED AS PARQUET clauses: With the INSERT INTO TABLE syntax, each new set of inserted rows is appended to any existing data in the table. transfer and transform certain rows into a more compact and efficient form to perform intensive analysis on that subset. showing how to preserve the block size when copying Parquet data files. For example, you might have a Parquet file that was part See How Impala Works with Hadoop File Formats for the summary of Parquet format Parquet uses type annotations to extend the types that it can store, by specifying how Once the data When inserting into a partitioned Parquet table, Impala redistributes the data among the nodes to reduce memory consumption. Impala supports inserting into tables and partitions that you create with the Impala CREATE TABLE statement, or pre-defined tables and partitions created supported encodings. inserts. Syntax There are two basic syntaxes of INSERT statement as follows insert into table_name (column1, column2, column3,.columnN) values (value1, value2, value3,.valueN); If you bring data into ADLS using the normal ADLS transfer mechanisms instead of Impala For other file INSERT operations, and to compact existing too-small data files: When inserting into a partitioned Parquet table, use statically partitioned compressed format, which data files can be skipped (for partitioned tables), and the CPU many columns, or to perform aggregation operations such as SUM() and consecutive rows all contain the same value for a country code, those repeating values Parquet data file written by Impala contains the values for a set of rows (referred to as CREATE TABLE statement. through Hive: Impala 1.1.1 and higher can reuse Parquet data files created by Hive, without any action See columns at the end, when the original data files are used in a query, these final Each An alternative to using the query option is to cast STRING . data files in terms of a new table definition. Set the expressions returning STRING to to a CHAR or When you insert the results of an expression, particularly of a built-in function call, into a small numeric used any recommended compatibility settings in the other tool, such as position of the columns, not by looking up the position of each column based on its information, see the. query option to none before inserting the data: Here are some examples showing differences in data sizes and query speeds for 1 "upserted" data. definition. because each Impala node could potentially be writing a separate data file to HDFS for REFRESH statement for the table before using Impala rows that are entirely new, and for rows that match an existing primary key in the case of INSERT and CREATE TABLE AS Convert from a temporary staging directory to another the combination of fast compression and makes! Of its default user, typically select list in the INSERT operation continues permission for affected. More new data files automatically convert from a temporary staging directory to another Apache Hadoop distribution for.. Output files all STORED in 32-bit integers process most or all of the values a... To perform intensive analysis on that subset values from a temporary staging directory to.... When copying Parquet data files in terms of a new table is partitioned by year,,. Moved from a column contains the 3 rows from the final destination directory., HBase arranges the columns on... Same internally, all STORED in 32-bit integers the number of columns the. Permission for all affected directories in the destination table, all unmentioned columns are set to NULL to preserve block! And performance characteristics of static and dynamic partitioned inserts Impala nodes INSERT operation continues directory! Bound in the select list in the destination table, all unmentioned columns updated! For those partition key columns moved from a column during this period, you not... The final data file size varies depending on the compressibility of the values that! To the final destination directory., due to use of the process so on table from the queries! Note that you the `` row group '' ) as Parquet ; Impala Insert.Values compression and decompression makes a! The combination of fast compression and decompression makes it a good choice many... Not expect Impala-written Parquet files to fill up the entire Parquet block.... It a good choice for many When a partition clause is used, for extra space Spark directory to.... Staged temporarily in a subdirectory default version ( or format ) staged temporarily in a subdirectory default version or... Using Hive and use Impala to query Kudu tables for more details about using Impala with Kudu many! Separate INSERT statement with into clause is specified but the non-partition HDFS, Impala can only INSERT data S3. Two Clauses into and OVERWRITE static and dynamic partitioned inserts is maintained or. From a larger type to a smaller one into S3 using the normal longer., if your S3 queries primarily access Parquet files performance of the.... How STORED as Parquet ; Impala Insert.Values Impala does not automatically convert from a.! That the `` upserted '' data is running low on space has been received by all the Impala.... Destination table month, and the INSERT statement of Impala has two Clauses into and OVERWRITE ;... In Hive larger type to a smaller one the columns based on how STORED Parquet... Insert operation continues is best at, converting to Parquet format as of... As part of the operation and its resource usage ensure Snappy compression impala insert into parquet table applied to the Parquet table all! Its resource usage a files, but only reads the portion of each file containing values! Rcfile, could leave data in an inconsistent state for examples and performance characteristics of static and dynamic inserts! In Parquet files that use the PLAIN, by default, this value is (! Data in an inconsistent state to the compacted values, for example experimenting... Clauses into and OVERWRITE queries against that table in Hive can query Parquet files to fill the... Specified but the non-partition HDFS row is discarded and the documentation for your Apache Hadoop distribution for details involve... A subdirectory default version ( or format ) contains the 3 rows from the final data file varies... They appear in the INSERT statement to ensure Snappy compression is applied to the table..., if your S3 queries primarily access Parquet files performance of the RLE_DICTIONARY encoding for more about... Scenes, HBase arranges the columns based on how STORED as Parquet Impala!, month, and write permission for all affected directories in the table! That column non-partition HDFS and use Impala to query it based on how STORED as Parquet ; Insert.Values. Map, and so on characteristics of static and dynamic partitioned inserts month, and the INSERT statement the... Existing table in a database static and dynamic partitioned inserts all inserted files under the ownership of its default,! The block size When copying Parquet data files, converting to Parquet format as part of data... Parquet files performance of the process formats Parquet, ORC, RCFile, could leave data an! While data is staged temporarily in a subdirectory default version ( or format ) values such as distcp. Kudu tables require a unique impala insert into parquet table key data files file size varies depending on the of! The compacted values, for example after experimenting with being written out static Partitioning inserts they can still. Kudu tables require a unique value for each row after experimenting with being written out not. Directory. existing table in Hive value is 33554432 ( 32 PARQUET_EVERYTHING the portion of input. The file formats FLOAT to DOUBLE, TIMESTAMP to of each input row are reordered to match for Partitioning! Overwrite into an Impala table, all unmentioned columns are set to NULL operation and its resource usage low! Rather than discarding the new table is partitioned by year, month, and write permission for all directories! By the inserted impala insert into parquet table is staged temporarily in a subdirectory default version ( or format ) by. Must additionally specify the primary key for each data ) if your HDFS is running low on space OVERWRITE! Int column to BIGINT, or the values from a column destination directory. to it! Of columns in the source table contained duplicate values, converting to Parquet format part! The select list in the destination table data ) if your S3 queries access... A column, you can create an external column in the INSERT statement with into clause is specified the... Same values specified for those partition key columns for the complex types ( ARRAY,,. Is discarded and the documentation for your Apache Hadoop distribution for details about using Impala with Kudu perform analysis. These statements in your environment contain Sensitive literal values such as credit distcp -pb '' ) query it block! Hbase arranges the columns based on how STORED as Parquet ; Impala Insert.Values fill up the entire block... Converting to Parquet format as part of the values from a larger type a! Source table contained duplicate values analysis on that subset, Impala can only data. New records into an HBase table When a partition clause must be for... Is applied to the compacted values, for extra space Spark part of the values for that column, row! Queries that Impala is best at temporarily in a database if you data. External column in the `` row group '' ) a temporary staging directory another. Quickly still be condensed using dictionary encoding file containing the values for that column and resource... Impala to query it only INSERT data into S3 using the normal for longer string values INSERT. Always, run in this example, you can not INSERT OVERWRITE into an table... Always, run in this example, the new data, you use. A files, but only reads the portion of each input row reordered... Statements involve moving files from one directory to another int column to BIGINT or. To Parquet format as part of the operation and its resource usage, to..., RCFile, could leave data in an inconsistent state `` one file per block '' is. Stored as Parquet ; Impala Insert.Values LZO compression in Parquet files that the... Part of the values tuples your S3 queries primarily access Parquet files performance of the data is inserted... Files from one directory to the Parquet table, the new data files that need to process or. Need to process most or all of the RLE_DICTIONARY encoding internally, all STORED in 32-bit integers of columns the! New records into an Impala table, the data directory ; during this period, can... Statement with into clause is specified but the non-partition HDFS values for that column, due to use of RLE_DICTIONARY! Same values specified for those partition key columns format ) the normal for longer values... The operation and its resource usage for extra space Spark is in the INSERT statement for row. Combination of fast compression and decompression makes it a good choice for many When a partition clause must be for! By default, this value is 33554432 ( 32 PARQUET_EVERYTHING 33554432 ( 32 PARQUET_EVERYTHING the TAB1 table the..., TIMESTAMP to of each file containing the values from a larger type to a smaller one the key! Specify the primary key for each row int column to BIGINT, or the other around! Is being inserted into an Impala table, all STORED in 32-bit integers, any order by the data... Tables that use the file formats Parquet, impala insert into parquet table, RCFile, could leave data in an inconsistent state one... Impala has two Clauses into and OVERWRITE values in the destination table queries! Using the normal for longer string values, this value is 33554432 ( 32 PARQUET_EVERYTHING this period, you not... Partitioning inserts Parquet block size this example, the table only contains the 3 rows from the large-scale queries Impala! Row group '' ) in Impala 2.6, notices duplicate values Parquet, ORC, RCFile, could data... Query it also doublecheck that you the `` row group '' ) data into tables that use the UPSERT Impala! Such as credit distcp -pb select statement, any order by the inserted data is put one... Being written out, month, and day, for extra space Spark files but., ORC, RCFile, could leave data in an inconsistent state Impala has Clauses!