=============== Ceph s3 select =============== .. contents:: Overview -------- | The purpose of the **s3 select** engine is to create an efficient pipe between user client and storage nodes (the engine should be close as possible to storage). | It enables selection of a restricted subset of (structured) data stored in an S3 object using an SQL-like syntax. | It also enables for higher level analytic-applications (such as SPARK-SQL) , using that feature to improve their latency and throughput. | For example, a s3-object of several GB (CSV file), a user needs to extract a single column which filtered by another column. | As the following query: | ``select customer-id from s3Object where age>30 and age<65;`` | Currently the whole s3-object must retrieve from OSD via RGW before filtering and extracting data. | By "pushing down" the query into OSD , it's possible to save a lot of network and CPU(serialization / deserialization). | **The bigger the object, and the more accurate the query, the better the performance**. Basic workflow -------------- | S3-select query is sent to RGW via `AWS-CLI `_ | It passes the authentication and permission process as an incoming message (POST). | **RGWSelectObj_ObjStore_S3::send_response_data** is the “entry point”, it handles each fetched chunk according to input object-key. | **send_response_data** is first handling the input query, it extracts the query and other CLI parameters. | Per each new fetched chunk (~4m), RGW executes s3-select query on it. | The current implementation supports CSV objects and since chunks are randomly “cutting” the CSV rows in the middle, those broken-lines (first or last per chunk) are skipped while processing the query. | Those “broken” lines are stored and later merged with the next broken-line (belong to the next chunk), and finally processed. | Per each processed chunk an output message is formatted according to `AWS specification `_ and sent back to the client. | RGW supports the following response: ``{:event-type,records} {:content-type,application/octet-stream} {:message-type,event}``. | For aggregation queries the last chunk should be identified as the end of input, following that the s3-select-engine initiates end-of-process and produces an aggregate result. Basic functionalities ~~~~~~~~~~~~~~~~~~~~~ | **S3select** has a definite set of functionalities that should be implemented (if we wish to stay compliant with AWS), currently only a portion of it is implemented. | The implemented software architecture supports basic arithmetic expressions, logical and compare expressions, including nested function calls and casting operators, that alone enables the user reasonable flexibility. | review the below feature-table_. Error Handling ~~~~~~~~~~~~~~ | Any error occurs while the input query processing, i.e. parsing phase or execution phase, is returned to client as response error message. | Fatal severity (attached to the exception) will end query execution immediately, other error severity are counted, upon reaching 100, it ends query execution with an error message. Features Support ---------------- .. _feature-table: | Currently only part of `AWS select command `_ is implemented, table bellow describes what is currently supported. | The following table describes the current implementation for s3-select functionalities: +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Feature | Detailed | Example | +=================================+=================+=======================================================================+ | Arithmetic operators | ^ * / + - ( ) | select (int(_1)+int(_2))*int(_9) from stdin; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | | | select ((1+2)*3.14) ^ 2 from stdin; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Compare operators | > < >= <= == != | select _1,_2 from stdin where (int(1)+int(_3))>int(_5); | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | logical operator | AND OR | select count(*) from stdin where int(1)>123 and int(_5)<200; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | casting operator | int(expression) | select int(_1),int( 1.2 + 3.4) from stdin; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | |float(expression)| select float(1.2) from stdin; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | | timestamp(...) | select timestamp("1999:10:10-12:23:44") from stdin; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Aggregation Function | sum | select sum(int(_1)) from stdin; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Aggregation Function | min | select min( int(_1) * int(_5) ) from stdin; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Aggregation Function | max | select max(float(_1)),min(int(_5)) from stdin; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Aggregation Function | count | select count(*) from stdin where (int(1)+int(_3))>int(_5); | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Timestamp Functions | extract | select count(*) from stdin where | | | | extract("year",timestamp(_2)) > 1950 | | | | and extract("year",timestamp(_1)) < 1960; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Timestamp Functions | dateadd | select count(0) from stdin where | | | | datediff("year",timestamp(_1),dateadd("day",366,timestamp(_1))) == 1; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Timestamp Functions | datediff | select count(0) from stdin where | | | | datediff("month",timestamp(_1),timestamp(_2))) == 2; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Timestamp Functions | utcnow | select count(0) from stdin where | | | | datediff("hours",utcnow(),dateadd("day",1,utcnow())) == 24 ; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | String Functions | substr | select count(0) from stdin where | | | | int(substr(_1,1,4))>1950 and int(substr(_1,1,4))<1960; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | alias support | | select int(_1) as a1, int(_2) as a2 , (a1+a2) as a3 | | | | from stdin where a3>100 and a3<300; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ s3-select function interfaces ----------------------------- Timestamp functions ~~~~~~~~~~~~~~~~~~~ | The `timestamp functionalities `_ is partially implemented. | the casting operator( ``timestamp( string )`` ), converts string to timestamp basic type. | Currently it can convert the following pattern ``yyyy:mm:dd hh:mi:dd`` | ``extract( date-part , timestamp)`` : function return integer according to date-part extract from input timestamp. | supported date-part : year,month,week,day. | ``dateadd(date-part , integer,timestamp)`` : function return timestamp, a calculation results of input timestamp and date-part. | supported data-part : year,month,day. | ``datediff(date-part,timestamp,timestamp)`` : function return an integer, a calculated result for difference between 2 timestamps according to date-part. | supported date-part : year,month,day,hours. | ``utcnow()`` : return timestamp of current time. Aggregation functions ~~~~~~~~~~~~~~~~~~~~~ | ``count()`` : return integer according to number of rows matching condition(if such exist). | ``sum(expression)`` : return a summary of expression per all rows matching condition(if such exist). | ``max(expression)`` : return the maximal result for all expressions matching condition(if such exist). | ``min(expression)`` : return the minimal result for all expressions matching condition(if such exist). String functions ~~~~~~~~~~~~~~~~ | ``substr(string,from,to)`` : return a string extract from input string according to from,to inputs. Alias ~~~~~ | **Alias** programming-construct is an essential part of s3-select language, it enables much better programming especially with objects containing many columns or in the case of complex queries. | Upon parsing the statement containing alias construct, it replaces alias with reference to correct projection column, on query execution time the reference is evaluated as any other expression. | There is a risk that self(or cyclic) reference may occur causing stack-overflow(endless-loop), for that concern upon evaluating an alias, it is validated for cyclic reference. | Alias also maintains result-cache, meaning upon using the same alias more than once, it’s not evaluating the same expression again(it will return the same result),instead it uses the result from cache. | Of Course, per each new row the cache is invalidated. Sending Query to RGW -------------------- | Any http-client can send s3-select request to RGW, it must be compliant with `AWS Request syntax `_. | Sending s3-select request to RGW using AWS cli, should follow `AWS command reference `_. | bellow is an example for it. :: aws --endpoint-url http://localhost:8000 s3api select-object-content --bucket {BUCKET-NAME} --expression-type 'SQL' --input-serialization '{"CSV": {"FieldDelimiter": "," , "QuoteCharacter": "\"" , "RecordDelimiter" : "\n" , "QuoteEscapeCharacter" : "\\" , "FileHeaderInfo": "USE" }, "CompressionType": "NONE"}' --output-serialization '{"CSV": {}}' --key {OBJECT-NAME} --expression "select count(0) from stdin where int(_1)<10;" output.csv Syntax ~~~~~~ | **Input serialization** (Implemented), it let the user define the CSV definitions; the default values are {\\n} for row-delimiter {,} for field delimiter, {"} for quote, {\\} for escape characters. | it handle the **csv-header-info**, the first row in input object containing the schema. | **Output serialization** is currently not implemented, the same for **compression-type**. | s3-select engine contain a CSV parser, which parse s3-objects as follows. | - each row ends with row-delimiter. | - field-separator separates between adjacent columns, successive field separator define NULL column. | - quote-character overrides field separator, meaning , field separator become as any character between quotes. | - escape character disables any special characters, except for row delimiter. | Below are examples for CSV parsing rules. CSV parsing behavior -------------------- +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Feature | Description | input ==> tokens | +=================================+=================+=======================================================================+ | NULL | successive | ,,1,,2, ==> {null}{null}{1}{null}{2}{null} | | | field delimiter | | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | QUOTE | quote character | 11,22,"a,b,c,d",last ==> {11}{22}{"a,b,c,d"}{last} | | | overrides | | | | field delimiter | | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | Escape | escape char | 11,22,str=\\"abcd\\"\\,str2=\\"123\\",last | | | overrides | ==> {11}{22}{str="abcd",str2="123"}{last} | | | meta-character. | | | | escape removed | | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | row delimiter | no close quote, | 11,22,a="str,44,55,66 | | | row delimiter is| ==> {11}{22}{a="str,44,55,66} | | | closing line | | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | csv header info | FileHeaderInfo | "**USE**" value means each token on first line is column-name, | | | tag | "**IGNORE**" value means to skip the first line | +---------------------------------+-----------------+-----------------------------------------------------------------------+ BOTO3 ----- | using BOTO3 is "natural" and easy due to AWS-cli support. :: def run_s3select(bucket,key,query,column_delim=",",row_delim="\n",quot_char='"',esc_char='\\',csv_header_info="NONE"): s3 = boto3.client('s3', endpoint_url=endpoint, aws_access_key_id=access_key, region_name=region_name, aws_secret_access_key=secret_key) r = s3.select_object_content( Bucket=bucket, Key=key, ExpressionType='SQL', InputSerialization = {"CSV": {"RecordDelimiter" : row_delim, "FieldDelimiter" : column_delim,"QuoteEscapeCharacter": esc_char, "QuoteCharacter": quot_char, "FileHeaderInfo": csv_header_info}, "CompressionType": "NONE"}, OutputSerialization = {"CSV": {}}, Expression=query,) result = "" for event in r['Payload']: if 'Records' in event: records = event['Records']['Payload'].decode('utf-8') result += records return result run_s3select( "my_bucket", "my_csv_object", "select int(_1) as a1, int(_2) as a2 , (a1+a2) as a3 from stdin where a3>100 and a3<300;")