要设置代码的方案，数据库会存储文档，并且每个文档都有可能将图像与其关联。
我一直在尝试编写一个查询数据库的路由，查找每个包含与其相关的图像的文档，将这些数据存储在JSON中，并在完成后返回到ajax请求，以便可以在页面上查看数据。我到目前为止最接近的是以下尝试（见代码）。
router.post('/advanced_image_search', userAuthenticated, function(req, res, next) {
async.waterfall([
// First function is to get each document which has an image related
function getDocuments(callback){
connection.query(`SELECT DISTINCT(Document.document_id), Document.doc_name, Document.doc_version_no, Document.doc_date_added
FROM Document WHERE doc_type = 'image'`, function(err, results) {
if (err) {
callback(err, null);
return;
}
// The Object containing the array where the data from the db needs to be stored
var documents = {
'docs': []
};
// foreach to iterate through each result found from the first db query (getDocuments)
results.forEach(function(result) {
// New object to store each document
var document = {};
document.entry = result;
// This is the array where each image assciated with a document will be stored
document.entry.images = [];
// Push each document to the array (above)
documents.docs.push(document);
var doc_id = result.document_id;
})
// Returning the results as 'documents' to the next function
callback(null, documents);
})
},
function getImages(documents, callback){
// Variable assignement to the array of documents
var doc_array = documents.docs;
// Foreach of the objects within document array
async.forEachOf(doc_array, function(doc, key, callback){
// Foreach object do the following series of functions
async.waterfall([
function handleImages(callback){
// The id of the document to get the images for
var doc_id = doc.entry.document_id;
connection.query(`SELECT * FROM Image, Document WHERE Image.document_id = '${doc_id}' AND Image.document_id = Document.document_id`, function(err, rows) {
if (err) {
callback(err, null);
return;
}
callback(null, rows);
})
},
// Function below to push each image to the document.entry.images array
//
function pushImages(rows, callback){
// If multiple images are found for that document, the loop iterates through each pushing to the images array
for (var j = 0; j < rows.length; j++) {
// Creating new object for each image found so the data can be stored within this object, then pushed into the images array
var image = {
'image_name': rows[j].image_name
};
doc.entry.images.push(image);
}
callback(null, doc_array);
}
], function(err, doc_array){
if (err) {
console.log('Error in second waterfall callback:')
callback(err);
return;
}
console.log(doc.entry);
// callback(null, doc_array);
})
}, function(err, doc_array){
if (err) {
callback(err);
return;
}
callback(null, doc_array);
});
callback(null, doc_array);
}
], function(err, doc_array) {
if (err){
console.log('Error is: '+err);
return;
}
// The response that should return each document with each related image in the JSON
res.send(doc_array);
})
});
目前返回的结果是：
1:
{entry: {document_id: 1, doc_name: "DocumentNameHere", doc_version_no: 1,…}}
entry:
{document_id: 1, doc_name: "DocumentNameHere", doc_version_no: 1,…}
doc_date_added:"2016-10-24"
doc_name:"DocumentNameHere"
doc_version_no:1
document_id:1
images:[]
从上面可以看出，即使通过测试，图像阵列仍然是空的，正在找到图像（console.log）。
我希望有人能够帮助解决这个问题，因为我正在努力找到这个复杂的问题。
由于
答案 0 :(得分：0)
这里有几个异步操作，每个操作都需要回调。见修改后的代码：
router.post('/advanced_image_search', userAuthenticated, function(req, res, next) {
var getDocuments = function(next) {
// Function for getting documents from DB
var query = `SELECT DISTINCT(Document.document_id), Document.doc_name, Document.doc_version_no, Document.doc_date_added FROM Document WHERE doc_type = 'image'`; // Set the query
connection.query(query, function(err, results) {
// Run the query async
if(err) {
// If err end execution
next(err, null);
return;
}
var documentList = []; // Array for holding docs
for(var i=0; i<results.length; i++) {
// Loop over results, construct the document and push to an array
var documentEntry = results[i];
var documentObject = {};
documentObject.entry = documentEntry;
documentObject.entry.images = [];
documentObject.id = documentEntry.document_id;
documentList.push(documentObject);
}
next(null, documents); // Pass to next async operation
});
};
var getImages = function(documents, next) {
// Function for getting images from documents
var finalDocs = []; // Blank arry for final documents with images
for (var i=0; i<documents.length; i++) {
// Loop over each document and construct the query
var id = documents[i].id;
var query = `SELECT * FROM Image, Document WHERE Image.document_id = '${doc_id}' AND Image.document_id = Document.document_id`;
connection.query(query, function(err, images) {
// Execute the query async
if(err) {
// Throw error to callback
next(err, null);
return;
}
var processedDoc = processImages(documents[i], images); // Call a helper function to process all images into the document object
finalDocs.push(processedDoc); // Push the processed doc
if(i === documents.length) {
// If there are no more documents move onto next async
next(null, finalDocs);
}
});
}
};
var processImages = function(doc, images) {
for (var i=0; i< images.length; i++) {
// Loop over each document image - construct object
var image = {
'image_name': rows[j].image_name
};
doc.entry.images.push(image); // Push image into document object
}
return doc; // Return processed doc
};
getDocuments(function(err, docs) {
if(err) {
// Your error handler
}
if(docs) {
getImages(docs, function(err, finalDocs) {
if(err) {
// Your error handler
}
if(finalDocs) {
console.log(finalDocs);
res.status(200).json(finalDocs); // Send response
}
});
}
});
});
其他说明
希望这有帮助
迪伦