How does knex handle default values in SQLite? - sql

We currently use mysql / knex, and I'm adding SQLite as a database for testing purposes. I'm getting
Knex:warning - sqlite does not support inserting default values. Set the useNullAsDefault flag to hide this warning. (see docs http://knexjs.org/#Builder-insert).
How does Knex handle default values? Does it just drop any defaults, or does it add in the defaults after an insert as following UPDATE statements?
I don't want to change all of our codebase (swap out all default values), trying to do the minimal change that will allow me to run SQLite in our tests... concerned this will introduce bugs.

I'm learning knex.js so I can use it in a project involving PostgreSQL. While trying out Sqlite I came across this issue.
Turns out it's documented!
If one prefers that undefined keys are replaced with NULL instead of DEFAULT one may give useNullAsDefault configuration parameter in knex config.
And they give this code:
var knex = require('knex')({
client: 'sqlite3',
connection: {
filename: "./mydb.sqlite"
},
useNullAsDefault: true
});
knex('coords').insert([{x: 20}, {y: 30}, {x: 10, y: 20}])
// insert into `coords` (`x`, `y`) values (20, NULL), (NULL, 30), (10, 20)"
This removed the warning message for me.

Related

Return inserted id with TypeORM & NestJS raw query: await connection.manager.query(`INSERT INTO

I'm looking to return the id or better yet, all information that was inserted, using a raw query with TypeORM and NestJS. Example as follows:
await connection.manager.query(`INSERT INTO...`)
When assigning the query to a constant and console logging it below, it does not yield any helpful information:
OkPacket {
fieldCount: 0,
affectedRows: 1,
insertId: 0,
serverStatus: 2,
warningCount: 1,
message: '',
protocol41: true,
changedRows: 0
}
As you can see, it returns no pertinent information, the insertId above is obviously incorrect, and it returns this every time, regardless of the actual parameters of the query.
I know with more typical TypeORM queries you can use .return(['name_of_column_you_want_returned']).execute()
and it will return the relevant information just fine. Is there any way to do this with a raw query? Thank you!
tl;dr You're getting the raw mariadb driver response (OkPacket) from the INSERT command, and you'd need a new SELECT query to see the data.
You're using the TypeORM EntityManager, and the docs don't mention a return value. Looking at the source code for query, the return type is any. Since it's a raw query, it probably returns an object based on the type of database you're using rather than having a standard format.
In this case, you're using MariaDb, which returned an OkPacket. Here's the documentation:
https://mariadb.com/kb/en/ok_packet/

MongoDB using $and with slice and a match

I'm using #Query from the spring data package and I want to query on the last element of an array in a document.
For example the data structure could be like this:
{
name : 'John',
scores: [10, 12, 14, 16]
},
{
name : 'Mary',
scores: [78, 20, 14]
},
So I've built a query, however it is complaining that "error message 'unknown operator: $slice' on server"
The $slice part of the query, when run separately, is fine:
db.getCollection('users').find({}, {scores: { $slice: -1 })
However as soon as I combine it with a more complex check, it gives the error as mentioned.
db.getCollection('users').find{{"$and":[{ } , {"scores" : { "$slice" : -1}} ,{"scores": "16"}]})
This query would return the list of users who had a last score of 16, in my example John would be returned but not Mary.
I've put it into a standard mongo query (to debug things), however ideally I need it to go into a spring-data #query construct - they should be fairly similar.
Is there anyway of doing this, without resorting to hand-cranked java calls? I don't see much documentation for #Query, other than it takes standard queries.
As commented with the link post, that refers to aggregate, how does that work with #Query, plus one of the main answers uses $where, this inefficient.
The general way forward with the problem is unfortunately the data, although #Veeram's response is correct, it will mean that you do not hit indexes. This is an issue where you've got very large data sets of course and you will see ever decreasing return times. It's something $where, $arrayElemAt cannot help you with. They have to pre-process the data and that means a full collection scan. We analysed several queries with these constructs and they involved a "COLSCAN".
The solution is ideally to create a field that contains the last item, for instance:
{
name : 'John',
scores: [10, 12, 14, 16],
lastScore: 16
},
{
name : 'Mary',
scores: [78, 20, 14],
lastScore: 14
}
You could create a listener to maintain this as follows:
#Component
public class ScoreListener extends AbstractMongoEventListener<Scores>
You then get the ability to sniff the data and make any updates:
#Override
public void onBeforeConvert(BeforeConvertEvent<Scores> event) {
// process any score and set lastScore
}
Don't forget to update your indexes (!):
#CompoundIndex(name = "lastScore", def = "{"
+ "'lastScore': 1"
+ " }")
Although this does contain a disadvantage of a slight duplication of data, in current Mongo (3.4) this really is the only way of doing this AND to include indexes in the search mechanism. The speed differences were dramatic, from nearly a minute response time down to milliseconds.
In Mongo 3.6 there may be better ways for doing that, however we are fixed on this version, so this has to be our solution.

BigQuery UDF Internal Error

We had a simple UDF in BigQuery that somehow throws an error that keeps returning
Query Failed
Error: An internal error occurred and the request could not be completed.
The query was simply trying to use UDF to perform a SHA256.
SELECT
input AS title,
input_sha256 AS title_sha256
FROM
SHA256(
SELECT
title AS input
FROM
[bigquery-public-data:hacker_news.stories]
GROUP BY
input
)
LIMIT
1000
The in-line UDF is pasted below. However I can not post the full UDF as StackOverflow complaints too much code in the post. The full UDF can be seen this gist.
function sha256(row, emit) {
emit(
{
input: row.input,
input_sha256: CryptoJS.SHA256(row.input).toString(CryptoJS.enc.Hex)
}
);
}
bigquery.defineFunction(
'SHA256', // Name of the function exported to SQL
['input'], // Names of input columns
[
{'name': 'input', 'type': 'string'},
{'name': 'input_sha256', 'type': 'string'}
],
sha256 // Reference to JavaScript UDF
);
Not sure if it helps, but the Job-ID is
bigquery:bquijob_7fd3b51c_153c058dc7c
Looks like there is a similar issue at:
https://code.google.com/p/google-bigquery/issues/detail?id=478
Short answer - this is an issue related to memory allocation that I uncovered via my own testing and fixed today, but it will take a little while to flow out to production.
Slightly longer answer - we just rolled out a fix today for an issue where users who were having "out of memory" issues when scaling up their UDFs over larger number of rows, even though the UDF would succeed on smaller numbers of rows. The queries that were hitting that condition are now running fine on our internal / test trees. However, since public BigQuery hosts have much higher traffic loads, the JavaScript engine that executes the UDFs (V8) behaves somewhat differently in production than it does in internal trees. Specifically, there's a new memory allocation error that some of the previously OOMing jobs are now hitting that we couldn't observe until the queries ran on a fully-loaded tree.
It's a minor error with a quick fix, but we'd ideally let it flow through our regular testing and QA cycle. This should put the fix in production in about a week, assuming nothing else goes wrong with the candidate. Would that be acceptable for you?
i am re-using answer box to provide full query text. it works if uncomment LIMIT 40
SELECT input, input_sha256 FROM JS(
(
SELECT title AS input
FROM [bigquery-public-data:hacker_news.stories]
GROUP BY input
//LIMIT 40
),
input,
"[ {'name': 'input', 'type': 'string'}, {'name': 'input_sha256', 'type': 'string'} ] ",
"function(row, emit) {
var CryptoJS=CryptoJS||function(h,s){var f={},g=f.lib={},q=function(){},m=g.Base={extend:function(a){q.prototype=this;var c=new q;a&&c.mixIn(a);c.hasOwnProperty('init')||(c.init=function(){c.$super.init.apply(this,arguments)});c.init.prototype=c;c.$super=this;return c},create:function(){var a=this.extend();a.init.apply(a,arguments);return a},init:function(){},mixIn:function(a){for(var c in a)a.hasOwnProperty(c)&&(this[c]=a[c]);a.hasOwnProperty('toString')&&(this.toString=a.toString)},clone:function(){return this.init.prototype.extend(this)}}, r=g.WordArray=m.extend({init:function(a,c){a=this.words=a||[];this.sigBytes=c!=s?c:4*a.length},toString:function(a){return(a||k).stringify(this)},concat:function(a){var c=this.words,d=a.words,b=this.sigBytes;a=a.sigBytes;this.clamp();if(b%4)for(var e=0;e<a;e++)c[b+e>>>2]|=(d[e>>>2]>>>24-8*(e%4)&255)<<24-8*((b+e)%4);else if(65535<d.length)for(e=0;e<a;e+=4)c[b+e>>>2]=d[e>>>2];else c.push.apply(c,d);this.sigBytes+=a;return this},clamp:function(){var a=this.words,c=this.sigBytes;a[c>>>2]&=4294967295<< 32-8*(c%4);a.length=h.ceil(c/4)},clone:function(){var a=m.clone.call(this);a.words=this.words.slice(0);return a},random:function(a){for(var c=[],d=0;d<a;d+=4)c.push(4294967296*h.random()|0);return new r.init(c,a)}}),l=f.enc={},k=l.Hex={stringify:function(a){var c=a.words;a=a.sigBytes;for(var d=[],b=0;b<a;b++){var e=c[b>>>2]>>>24-8*(b%4)&255;d.push((e>>>4).toString(16));d.push((e&15).toString(16))}return d.join('')},parse:function(a){for(var c=a.length,d=[],b=0;b<c;b+=2)d[b>>>3]|=parseInt(a.substr(b, 2),16)<<24-4*(b%8);return new r.init(d,c/2)}},n=l.Latin1={stringify:function(a){var c=a.words;a=a.sigBytes;for(var d=[],b=0;b<a;b++)d.push(String.fromCharCode(c[b>>>2]>>>24-8*(b%4)&255));return d.join('')},parse:function(a){for(var c=a.length,d=[],b=0;b<c;b++)d[b>>>2]|=(a.charCodeAt(b)&255)<<24-8*(b%4);return new r.init(d,c)}},j=l.Utf8={stringify:function(a){try{return decodeURIComponent(escape(n.stringify(a)))}catch(c){throw Error('Malformed UTF-8 data');}},parse:function(a){return n.parse(unescape(encodeURIComponent(a)))}}, u=g.BufferedBlockAlgorithm=m.extend({reset:function(){this._data=new r.init;this._nDataBytes=0},_append:function(a){'string'==typeof a&&(a=j.parse(a));this._data.concat(a);this._nDataBytes+=a.sigBytes},_process:function(a){var c=this._data,d=c.words,b=c.sigBytes,e=this.blockSize,f=b/(4*e),f=a?h.ceil(f):h.max((f|0)-this._minBufferSize,0);a=f*e;b=h.min(4*a,b);if(a){for(var g=0;g<a;g+=e)this._doProcessBlock(d,g);g=d.splice(0,a);c.sigBytes-=b}return new r.init(g,b)},clone:function(){var a=m.clone.call(this); a._data=this._data.clone();return a},_minBufferSize:0});g.Hasher=u.extend({cfg:m.extend(),init:function(a){this.cfg=this.cfg.extend(a);this.reset()},reset:function(){u.reset.call(this);this._doReset()},update:function(a){this._append(a);this._process();return this},finalize:function(a){a&&this._append(a);return this._doFinalize()},blockSize:16,_createHelper:function(a){return function(c,d){return(new a.init(d)).finalize(c)}},_createHmacHelper:function(a){return function(c,d){return(new t.HMAC.init(a, d)).finalize(c)}}});var t=f.algo={};return f}(Math);
(function(h){for(var s=CryptoJS,f=s.lib,g=f.WordArray,q=f.Hasher,f=s.algo,m=[],r=[],l=function(a){return 4294967296*(a-(a|0))|0},k=2,n=0;64>n;){var j;a:{j=k;for(var u=h.sqrt(j),t=2;t<=u;t++)if(!(j%t)){j=!1;break a}j=!0}j&&(8>n&&(m[n]=l(h.pow(k,0.5))),r[n]=l(h.pow(k,1/3)),n++);k++}var a=[],f=f.SHA256=q.extend({_doReset:function(){this._hash=new g.init(m.slice(0))},_doProcessBlock:function(c,d){for(var b=this._hash.words,e=b[0],f=b[1],g=b[2],j=b[3],h=b[4],m=b[5],n=b[6],q=b[7],p=0;64>p;p++){if(16>p)a[p]= c[d+p]|0;else{var k=a[p-15],l=a[p-2];a[p]=((k<<25|k>>>7)^(k<<14|k>>>18)^k>>>3)+a[p-7]+((l<<15|l>>>17)^(l<<13|l>>>19)^l>>>10)+a[p-16]}k=q+((h<<26|h>>>6)^(h<<21|h>>>11)^(h<<7|h>>>25))+(h&m^~h&n)+r[p]+a[p];l=((e<<30|e>>>2)^(e<<19|e>>>13)^(e<<10|e>>>22))+(e&f^e&g^f&g);q=n;n=m;m=h;h=j+k|0;j=g;g=f;f=e;e=k+l|0}b[0]=b[0]+e|0;b[1]=b[1]+f|0;b[2]=b[2]+g|0;b[3]=b[3]+j|0;b[4]=b[4]+h|0;b[5]=b[5]+m|0;b[6]=b[6]+n|0;b[7]=b[7]+q|0},_doFinalize:function(){var a=this._data,d=a.words,b=8*this._nDataBytes,e=8*a.sigBytes; d[e>>>5]|=128<<24-e%32;d[(e+64>>>9<<4)+14]=h.floor(b/4294967296);d[(e+64>>>9<<4)+15]=b;a.sigBytes=4*d.length;this._process();return this._hash},clone:function(){var a=q.clone.call(this);a._hash=this._hash.clone();return a}});s.SHA256=q._createHelper(f);s.HmacSHA256=q._createHmacHelper(f)})(Math);
(function(){var h=CryptoJS,j=h.lib.WordArray;h.enc.Base64={stringify:function(b){var e=b.words,f=b.sigBytes,c=this._map;b.clamp();b=[];for(var a=0;a<f;a+=3)for(var d=(e[a>>>2]>>>24-8*(a%4)&255)<<16|(e[a+1>>>2]>>>24-8*((a+1)%4)&255)<<8|e[a+2>>>2]>>>24-8*((a+2)%4)&255,g=0;4>g&&a+0.75*g<f;g++)b.push(c.charAt(d>>>6*(3-g)&63));if(e=c.charAt(64))for(;b.length%4;)b.push(e);return b.join('')},parse:function(b){var e=b.length,f=this._map,c=f.charAt(64);c&&(c=b.indexOf(c),-1!=c&&(e=c));for(var c=[],a=0,d=0;d< e;d++)if(d%4){var g=f.indexOf(b.charAt(d-1))<<2*(d%4),h=f.indexOf(b.charAt(d))>>>6-2*(d%4);c[a>>>2]|=(g|h)<<24-8*(a%4);a++}return j.create(c,a)},_map:'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/='}})();
emit( { input: row.input, input_sha256: CryptoJS.SHA256(row.input).toString(CryptoJS.enc.Hex) } );
}"
)

Reading data from SQL Server using Spark SQL

Is it possible to read data from Microsoft Sql Server (and oracle, mysql, etc.) into an rdd in a Spark application? Or do we need to create an in memory set and parallize that into an RDD?
In Spark 1.4.0+ you can now use sqlContext.read.jdbc
That will give you a DataFrame instead of an RDD of Row objects.
The equivalent to the solution you posted above would be
sqlContext.read.jdbc("jdbc:sqlserver://omnimirror;databaseName=moneycorp;integratedSecurity=true;", "TABLE_NAME", "id", 1, 100000, 1000, new java.util.Properties)
It should pick up the schema of the table, but if you'd like to force it, you can use the schema method after read sqlContext.read.schema(...insert schema here...).jdbc(...rest of the things...)
Note that you won't get an RDD of SomeClass here (which is nicer in my view). Instead you'll get a DataFrame of the relevant fields.
More information can be found here: http://spark.apache.org/docs/latest/sql-programming-guide.html#jdbc-to-other-databases
Found a solution to this from the mailing list. JdbcRDD can be used to accomplish this. I needed to get the MS Sql Server JDBC driver jar and add it to the lib for my project. I wanted to use integrated security, and so needed to put sqljdbc_auth.dll (available in the same download) in a location that java.library.path can see. Then, the code looks like this:
val rdd = new JdbcRDD[Email](sc,
() => {DriverManager.getConnection(
"jdbc:sqlserver://omnimirror;databaseName=moneycorp;integratedSecurity=true;")},
"SELECT * FROM TABLE_NAME Where ? < X and X < ?",
1, 100000, 1000,
(r:ResultSet) => { SomeClass(r.getString("Col1"),
r.getString("Col2"), r.getString("Col3")) } )
This gives an Rdd of SomeClass.The second, third and fourth parameters are required and are for lower and upper bounds, and number of partitions. In other words, that source data needs to be partitionable by longs for this to work.

How to set up an insert to a grails created file with next sequence number?

I'm using a JMS queue to read from and insert data into a postgres table created by grails. The problem is obtaining the next sequence value. I thought I had found the solution with the following statement (by putting "DEFAULT" where the ID should go), but it's no longer working. I must have changed something, because I needed to recreate the table. What's the best way to get around this problem?
ps = c.prepareStatement("INSERT INTO xml_test (id, version, xml_text)
VALUES (DEFAULT, 0, ?)");
UPDATE:
In response to the suggested solution, I did the following:
Added this to the the domain:
class XmlTest {
String xmlText
static constraints = {
id generator:'sequence', params:[name:'xmltest_sequence']
}
}
And changed the insert statement to the following:
ps = c.prepareStatement("INSERT INTO xml_test (id, version, xml_text)
VALUES (nextval('xmltest_sequence'), 0, ?)");
However, when I run the statement, I get the following error:
[java] 1 org.postgresql.util.PSQLException: ERROR: relation "xmltest_sequence" does not exist
Any thoughts?
You can get the value of any sequence in PostgreSQL using nextval function, in your case:
INSERT INTO xml_test (id, version, xml_text) VALUES (nextval('sequence_name_for_this_table'), 0, ?);
And in your grails domain class you can choose the sequence name:
static mapping = {
id generator:sequence, params:[name:'sequence_name_for_this_table']
}
Problem solved.
It turns out that when grails creates a table, it doesn't assign a specific sequence generator to it.
Instead, grails uses a single sequence generator for all tables. This is called "hibernate_sequence".
So, to get around the problem, I included the "nextval" for that in my SQL statement:
ps = c.prepareStatement("INSERT INTO xml_test (id, version, text_field) VALUES (nextval('hibernate_sequence'), 0, ?)");