=============== Ceph s3 select =============== .. contents:: Overview -------- | The purpose of **s3 select** engine is to create an efficient pipe between user client to storage node (the engine should be close as possible to storage). | It enables the user to define the exact portion of data should be received by his side. | 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), it runs the s3-select query on that chunk. | 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. | 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. Design Concepts --------------- AST- Abstract Syntax Tree ~~~~~~~~~~~~~~~~~~~~~~~~~ | The s3-select main flow is initiated with parsing of input-string (i.e user query), and follows | with building an AST (abstract-syntax-tree) as a result. | The execution phase is built upon the AST. | ``Base_statement`` is the base for the all object-nodes participating in the execution phase, it consists of the ``eval()`` method which returns the object. | ``value`` object is handling the known basic-types such as int,string,float,time-stamp | It is able to operate comparison and basic arithmetic operations on mentioned types. | The execution-flow is actually calling the ``eval()`` method on the root-node (per each projection), it goes all the way down, and returns the actual result (``value`` object) from bottom node to root node(all the way up) . | **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 the correct AST-node, on runtime the node is simply evaluated as any other node. | 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 node again(it will return the same result),instead it uses the result from cache. | Of Course, per each new row the cache is invalidated. S3 select parser definition ~~~~~~~~~~~~~~~~~~~~~~~~~~~ | The implementation of s3-select uses the `boost::spirit `_ the definition of s3-select command is according to AWS. | Upon parsing is initiated on input text, and a specific rule is identified, an action which is bound to that rule is executed. | Those actions are building the AST, each action is unique (as its rule), at the end of the process it forms a structure similar to a tree. | As mentioned, running eval() on the root node, execute the s3-select statement (per projection). | The input stream is accessible to the execution tree, by the scratch-area object, that object is constantly updated per each new row. 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 bellow feature-table_. Memory handling ~~~~~~~~~~~~~~~ | S3select structures and objects are lockless and thread-safe, it uses placement-new in order to reduce the alloc/dealloc intensive cycles, which may impact the main process hosting s3-select. | Once AST is built there is no need to allocate memory for the execution itself, the AST is “static” for the query-execution life-cycle. | The execution itself is stream-oriented, meaning there is no pre-allocation before execution, object size has no impact on memory consumption. | It processes chunk after chunk, row after row, all memory needed for processing resides on AST. | The AST is similar to stack behaviour in that it consumes already allocated memory and “releases” it upon completing its task. S3 Object different types ~~~~~~~~~~~~~~~~~~~~~~~~~ | The processing of input stream is decoupled from s3-select-engine, meaning , each input-type should have its own parser, converting s3-object into columns. | Current implementation includes only CSV reader; its parsing definitions are according to AWS. | The parser is implemented using `boost::state-machine `_. | The CSV parser handles NULL,quote,escape rules,field delimiter,row delimiter and users may define (via AWS CLI) all of those dynamically. Error Handling ~~~~~~~~~~~~~~ | S3-select statement may be syntactically correct but semantically wrong, for one example ``select a * b from …`` , where a is number and b is a string. | Current implementation is for CSV file types, CSV has no schema, column-types may evaluate on runtime. | The above means that wrong semantic statements may occur on runtime. | As for syntax error ``select x frm stdin;`` , the builtin parser fails on first miss-match to language definition, and produces an error message back to client (AWS-CLI). | The error message is point on location of miss-match. | Fatal severity (attached to the exception) will end execution immediately, other error severity are counted, upon reaching 100, it ends execution with an error message. AST denostration ~~~~~~~~~~~~~~~~ .. ditaa:: +---------------------+ | select | +------ +---------------------+---------+ | | | | | | | | | | V | | +--------------------+ | | | s3object | | | +--------------------+ | | | V V +---------------------+ +-------------+ | projections | | where | +---------------------+ +-------------+ | | | | | | | | | | | | | | | | | | V V V +-----------+ +-----------+ +-------------+ | multiply | | date | | and | +-----------+ +-----------+ +-------------+ | | | | | | | | | | | | | | | | V V V V +-------+ +-------+ +-----+ +-----+ |payment| | 0.3 | | EQ | | LT | +-------+ +-------+ +--+-----+ +-----+--+ | | | | | | | | V V V V +-------+ +----+ +-----+ +-----+ | region| |east| |age | | 30 | +-------+ +----+ +-----+ +-----+ Features Support ---------------- .. _feature-table: The following table describes the support 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)| | +---------------------------------+-----------------+-----------------------------------------------------------------------+ | | 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; | +---------------------------------+-----------------+-----------------------------------------------------------------------+ Sending Query to RGW -------------------- Syntax ~~~~~~ CSV default defintion for field-delimiter,row-delimiter,quote-char,escape-char are: { , \\n " \\ } :: 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 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 | +---------------------------------+-----------------+-----------------------------------------------------------------------+